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  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Hepatoma Res.</journal-id>
      <journal-id journal-id-type="publisher-id">HR</journal-id>
      <journal-title-group>
        <journal-title>Hepatoma Research</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2454-2520</issn>
      <publisher>
        <publisher-name>OAE Publishing Inc.</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.20517/2394-5079.2025.77</article-id>
      <article-categories>
        <subj-group>
          <subject>Systematic Review</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>A systematic review of comparative economic analyses of systemic therapies for hepatocellular carcinoma</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>De Simone</surname>
            <given-names>Paolo</given-names>
          </name>
          <xref ref-type="aff" rid="I1">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="I2">
            <sup>2</sup>
          </xref>
          <xref ref-type="corresp" rid="cor1" />
          <contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6713-6170</contrib-id>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Peritore</surname>
            <given-names>Daniela</given-names>
          </name>
          <xref ref-type="aff" rid="I3">
            <sup>3</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ducci</surname>
            <given-names>Juri</given-names>
          </name>
          <xref ref-type="aff" rid="I4">
            <sup>4</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Romano</surname>
            <given-names>Lucia</given-names>
          </name>
          <xref ref-type="aff" rid="I5">
            <sup>5</sup>
          </xref>
          <xref ref-type="aff" rid="I6">
            <sup>6</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Longo</surname>
            <given-names>Donato</given-names>
          </name>
          <xref ref-type="aff" rid="I7">
            <sup>7</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Giuliani</surname>
            <given-names>Antonio</given-names>
          </name>
          <xref ref-type="aff" rid="I5">
            <sup>5</sup>
          </xref>
          <xref ref-type="aff" rid="I6">
            <sup>6</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Campani</surname>
            <given-names>Daniela</given-names>
          </name>
          <xref ref-type="aff" rid="I2">
            <sup>2</sup>
          </xref>
          <xref ref-type="aff" rid="I8">
            <sup>8</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Vistoli</surname>
            <given-names>Fabio</given-names>
          </name>
          <xref ref-type="aff" rid="I5">
            <sup>5</sup>
          </xref>
          <xref ref-type="aff" rid="I6">
            <sup>6</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="I1">
        <sup>1</sup>Liver Transplant Program, University of Pisa Medical School Hospital, Pisa 56124, Italy.</aff>
      <aff id="I2">
        <sup>2</sup>Department of Surgical, Medical, Biomolecular Pathology and Intensive Care, University of Pisa, Pisa 56126, Italy.</aff>
      <aff id="I3">
        <sup>3</sup>Italian National Center for Transplantation, Rome 00162, Italy.</aff>
      <aff id="I4">
        <sup>4</sup>Day-Surgery Unit, Pisa University Hospital, Pisa 56124, Italy.</aff>
      <aff id="I5">
        <sup>5</sup>Division of General Surgery and Transplantation, San Salvatore Hospital, L’Aquila 67100, Italy.</aff>
      <aff id="I6">
        <sup>6</sup>Department of Applied and Biotechnological Clinical Sciences, University of L’Aquila, L’Aquila 67100, Italy.</aff>
      <aff id="I7">
        <sup>7</sup>Intensive Care Unit, Vito Fazzi Hospital, Lecce 73100, Italy.</aff>
      <aff id="I8">
        <sup>8</sup>Pathology Department, Pisa University Hospital, Pisa 56124, Italy.</aff>
      <author-notes>
        <corresp id="cor1">Correspondence to: Dr. Paolo De Simone, Liver Transplant Program, University of Pisa Medical School Hospital, Pisa 56124, Italy. E-mail: <email>paolo.desimone@unipi.it</email></corresp>
        <fn fn-type="other">
          <p>
            <bold>Received:</bold> 7 Oct 2025 | <bold>First Decision:</bold> 15 Jan 2026 | <bold>Revised:</bold> 12 Mar 2026 | <bold>Accepted:</bold> 10 Apr 2026 | <bold>Published:</bold> 10 Jun 2026</p>
        </fn>
        <fn fn-type="other">
          <p>
            <bold>Academic Editor:</bold> Chunfeng Qu | <bold>Copy Editor:</bold> Ting-Ting Hu | <bold>Production Editor:</bold> Ting-Ting Hu</p>
        </fn>
      </author-notes>
      <pub-date pub-type="ppub">
        <year>2026</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>10</day>
        <month>6</month>
        <year>2026</year>
      </pub-date>
      <volume>12</volume>
	  <elocation-id>27</elocation-id>
      <permissions>
        <copyright-statement>© The Author(s) 2026.</copyright-statement>
        <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
          <license-p>© The Author(s) 2026. <bold>Open Access</bold> This article is licensed under a Creative Commons Attribution 4.0 International License (<uri xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</uri>), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.</license-p>
        </license>
      </permissions>
      <abstract>
        <p>
          <bold>Aim:</bold> We conducted a systematic synthesis of comparative economic evaluations assessing systemic therapies for hepatocellular carcinoma (HCC) to establish their cost-effectiveness.</p>
        <p>
          <bold>Methods:</bold> We searched six bibliographic databases for English-language studies published from 2015 through June 2025. Extracted endpoints included counts and types of regimens deemed cost-effective, quality-adjusted life years (QALYs), incremental cost-effectiveness ratios (ICERs), and ICER relative to national willingness-to-pay (WTP) thresholds.</p>
        <p>
          <bold>Results:</bold> Fifty-four studies met the inclusion criteria, producing four treatment subgroupings and 35 distinct treatment comparisons. QALYs were reported in 96.3% of articles, ICERs in 90.7%, and WTP thresholds in 92.6%. Fourteen regimens (40.0% of comparisons) were judged cost-effective. Regimens that included immunotherapy were more often cost-effective, while lenvatinib outperformed sorafenib in most analyses. Nearly all studies (94.4%) relied, to varying degrees, on data from 14 randomized controlled trials; 48.1% focused on the Chinese healthcare environment; 27.8% used a lifetime horizon; and 38.9% reported a median [interquartile range (IQR)] horizon of 10 (9) years. Only 5.5% adopted a societal perspective.</p>
        <p>
          <bold>Conclusion:</bold> Less than half of the evaluated systemic therapies were cost-effective, focusing mainly on immunotherapy-based regimens. Harmonized methodological standards are needed to ensure that economic evaluations keep pace with real-world practice as systemic treatments become more widely adopted. [International Platform of Systematic Review and Meta-Analysis Protocols (INPLASY) registration number: 2025100049].</p>
      </abstract>
      <kwd-group>
        <kwd>Hepatocellular carcinoma</kwd>
        <kwd>treatment</kwd>
        <kwd>systemic therapy</kwd>
        <kwd>immunotherapy</kwd>
        <kwd>oral agents</kwd>
        <kwd>cost</kwd>
        <kwd>cost-effectiveness</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec1">
      <title>INTRODUCTION</title>
      <p>Understanding the costs and cost drivers of medical treatments is vital to maintaining the viability of modern health systems in an era of constrained resources<sup>[<xref ref-type="bibr" rid="B1">1</xref>]</sup>. This concern is especially acute in oncology, where rising expenditures do not always correspond to substantial improvements in survival or quality of life<sup>[<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B3">3</xref>]</sup>. Containing healthcare spending remains a persistent challenge, and expenditures are expected to continue climbing<sup>[<xref ref-type="bibr" rid="B4">4</xref>]</sup>.</p>
      <p>Management of hepatocellular carcinoma (HCC) now spans image-guided procedures, surgical resection, liver transplantation (LT), systemic drugs, and multimodal combinations<sup>[<xref ref-type="bibr" rid="B5">5</xref>-<xref ref-type="bibr" rid="B7">7</xref>]</sup>, with associated costs steadily increasing<sup>[<xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B9">9</xref>]</sup>. One cost-control approach is to match patients to the therapies most likely to achieve a cure, prioritizing treatments with curative potential regardless of cost<sup>[<xref ref-type="bibr" rid="B1">1</xref>]</sup>. Another strategy emphasizes earlier diagnosis and rapid initiation of care<sup>[<xref ref-type="bibr" rid="B1">1</xref>]</sup>. Global surveillance recommendations for patients with chronic liver disease have improved early tumor detection and the chance for curative therapy<sup>[<xref ref-type="bibr" rid="B10">10</xref>]</sup>. Screening of asymptomatic high-risk individuals can uncover HCC at stages suitable for potentially curative interventions<sup>[<xref ref-type="bibr" rid="B11">11</xref>,<xref ref-type="bibr" rid="B12">12</xref>]</sup> thereby reducing treatment costs and improving outcomes<sup>[<xref ref-type="bibr" rid="B8">8</xref>]</sup>.</p>
      <p>Over the last decade, systemic options for HCC have expanded to include oral targeted therapies, tyrosine kinase inhibitors (TKIs), vascular endothelial growth factor (VEGF) pathway inhibitors (VEGFi), and immune checkpoint inhibitors (ICIs)<sup>[<xref ref-type="bibr" rid="B13">13</xref>]</sup>. Agents that improve response rates, progression-free survival (PFS), and overall survival (OS) have become first-line choices for advanced (aHCC), unresectable (uHCC), or metastatic (mHCC) HCC<sup>[<xref ref-type="bibr" rid="B14">14</xref>]</sup>. They are also being integrated in combined or sequential approaches with interventional radiology to pursue curative aims, facilitate conversion to resection, or serve as adjuvant/neoadjuvant therapies<sup>[<xref ref-type="bibr" rid="B15">15</xref>,<xref ref-type="bibr" rid="B16">16</xref>]</sup>.</p>
      <p>Despite their clinical importance, formal economic evaluations are mostly missing from major HCC management guidelines. The Barcelona Clinic Liver Cancer (BCLC)<sup>[<xref ref-type="bibr" rid="B5">5</xref>]</sup>, the Japanese Society of Hepatology-HCC (JSH-HCC)<sup>[<xref ref-type="bibr" rid="B17">17</xref>]</sup>, the Chinese guidelines<sup>[<xref ref-type="bibr" rid="B18">18</xref>]</sup>, the European Association for the Study of the Liver (EASL)<sup>[<xref ref-type="bibr" rid="B19">19</xref>]</sup>, and the American Association for the Study of Liver Disease (AASLD)<sup>[<xref ref-type="bibr" rid="B20">20</xref>]</sup> do not systematically include cost-effectiveness analyses. Differences in costing methods across studies, countries, and systems make it difficult to include economic data in effectiveness research. However, gaining a better understanding of the financial factors affecting HCC management could help clinicians make informed decisions within budget limits and involve administrators, payers, policymakers, patients, and other stakeholders in the process.</p>
      <p>To address this gap, we reviewed comparative economic studies of contemporary HCC therapies, exploring differences by patient characteristics, tumor stage, institution, and geography. This paper concentrates on systemic agents used as first- or second-line therapies for advanced HCC.</p>
    </sec>
    <sec id="sec2">
      <title>METHODS</title>
      <sec id="sec2-1">
        <title>Research design</title>
        <p>This work is a systematic review of comparative economic evaluations of therapeutic approaches for HCC. The interpretation of review findings draws upon the principles described by Sukhera in 2022<sup>[<xref ref-type="bibr" rid="B21">21</xref>]</sup>. This approach was selected to provide a critical, sometimes subjective appraisal of available evidence and to offer perspectives on how the field might progress from diverse vantage points<sup>[<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B22">22</xref>]</sup>. Accordingly, we followed the five key steps outlined in prior publications<sup>[<xref ref-type="bibr" rid="B21">21</xref>-<xref ref-type="bibr" rid="B23">23</xref>]</sup>.</p>
        <sec id="sec2-1-1">
          <title>Rationale for the review</title>
          <p>Evaluating the cost-effectiveness of HCC treatments is crucial for guiding clinical decisions. As new drugs and regimens are introduced rapidly, assessments of the economic value of systemic therapies need frequent updates<sup>[<xref ref-type="bibr" rid="B5">5</xref>,<xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B15">15</xref>]</sup>. The goals of this study were to gather evidence on: (1) the comparative economic effectiveness, utility, and benefits of HCC treatment options; and (2) factors that influence treatment costs, including perspectives from clinicians, hospital managers, policymakers, patients, and stakeholders. The review also examined international differences in financial aspects among providers, payers, and regions. In this scope, we specifically focused on first- and second-line systemic therapies.</p>
        </sec>
        <sec id="sec2-1-2">
          <title>Research question</title>
          <p>The primary research question of the entire project was: What are the most cost-effective treatments for patients with HCC?</p>
          <p>Within this framework, the research question of the current study was: What are the most cost-effective first- and second-line systemic therapies for patients with HCC?</p>
        </sec>
        <sec id="sec2-1-3">
          <title>Boundaries and definitions</title>
          <p>We used the P (patients/disease), I (interventions), C (comparators), and O (outcomes) framework, where patients were those affected by HCC; interventions included all active strategies for treating HCC, both curative and palliative; comparisons involved best supportive care (BSC) or comparisons across treatments; and outcomes measured economic treatment metrics. Therapeutic interventions were based on the 2025 EASL guidelines for HCC treatment. These were categorized into (1) ablation; (2) intra-arterial therapies; and (3) systemic therapies<sup>[<xref ref-type="bibr" rid="B19">19</xref>]</sup>. Ablation includes conventional or drug-enhanced radiofrequency ablation (RFA) or microwave ablation (MW), selective internal radiotherapy (SIRT), stereotactic body radiation therapy (SBRT), liver resection (LR), and LT. Intra-arterial therapies included hepatic artery infusion chemotherapy (HAIC) and trans-arterial chemoembolization (TACE). We also expanded the research to include treatments not yet fully explored by the EASL guidelines, such as carbon ion therapy (CIT). Based on the available studies, these treatments were considered either alone or in combination.</p>
          <p>Comparative economic evaluations were defined per international standards as cost-minimization analysis (CMA), cost-benefit analysis (CBA), cost-effectiveness analysis (CEA), cost-utility analysis (CUA), and cost-of-illness analysis (COIA)<sup>[<xref ref-type="bibr" rid="B24">24</xref>,<xref ref-type="bibr" rid="B25">25</xref>]</sup>. COIA papers were excluded because they lacked a comparator population<sup>[<xref ref-type="bibr" rid="B25">25</xref>,<xref ref-type="bibr" rid="B26">26</xref>]</sup>. Considerable overlap exists among these methods, particularly between CEA and CUA, and classifications vary across authors<sup>[<xref ref-type="bibr" rid="B27">27</xref>-<xref ref-type="bibr" rid="B29">29</xref>]</sup>.</p>
        </sec>
        <sec id="sec2-1-4">
          <title>Inclusion criteria</title>
          <p>PubMed (PubMed.gov), Google Scholar (<uri xlink:href="https://scholar.google.com/">https://scholar.google.com/</uri>), Cochrane (Wiley Online), Scopus, Web of Science (WoS), and Embase (Embase.com) were searched on July 1, 2025. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines were used to define the study’s eligibility criteria, conduct quality assessment, and analyze the results<sup>[<xref ref-type="bibr" rid="B30">30</xref>,<xref ref-type="bibr" rid="B31">31</xref>]</sup>. A PRISMA checklist for the abstract and paper is provided as <inline-supplementary-material content-type="local-data" mimetype="application/pdf" xlink:href="hr11077-SupplementaryMaterials.pdf">Supplementary Materials</inline-supplementary-material>.</p>
          <p>The search terms used to retrieve the studies are illustrated in the <inline-supplementary-material content-type="local-data" mimetype="application/pdf" xlink:href="hr11077-SupplementaryMaterials.pdf">Supplementary Materials</inline-supplementary-material>. Only full-length articles in English or in English translations were included. Systematic reviews, commentaries, empirical articles, gray literature, trade publications, and digital media communications were excluded and used only to retrieve additional references not included in the original search strategy. Owing to various factors, such as the rising healthcare costs of HCC treatment<sup>[<xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B8">8</xref>]</sup>, advancements in recent medical technologies for HCC, shifts in liver disease epidemiology with the emergence of metabolic dysfunction-associated liver disease (MASLD), and the increasing number of publications on HCC, the literature review was limited to studies published between 2015 and June 30, 2025. However, if the thematic coverage was insufficient, a second search was conducted without date restrictions, and key or seminal papers on the topic, along with other relevant manuscripts, were considered, regardless of their publication date.</p>
          <p>Only articles comparing first- or second-line systemic treatments to active comparators, placebo, or BSC were included in the final analysis. Studies involving neoadjuvant or adjuvant therapies administered before or after radiology-assisted interventions or surgery, and systemic therapies compared with intrahepatic arterial infusion, were excluded.</p>
          <p>The references were initially evaluated independently by two investigators (Longo D and De Simone P) based on the face value of their abstracts, with any disagreements resolved by a third reviewer (Peritore D). The reference lists of the articles were also checked for additional literature (snowballing). An artificial intelligence (AI)-based Rayyan platform was used to sort articles, assess abstracts and texts, and eliminate duplicates (<uri xlink:href="https://www.rayyan.ai/">https://www.rayyan.ai/</uri>). A shared Google Drive repository was used to collect and review articles from all team members.</p>
        </sec>
        <sec id="sec2-1-5">
          <title>Data extraction and interpretation</title>
          <p>Extracted variables included year, authors, title, study type, country, population, interventions and comparators, and effectiveness measures [quality-adjusted life-years (QALYs) or life-years saved (LYS)]. Costing methods, time horizons, discount rates, currencies, sensitivity analyses, reported costs, and economic metrics were also recorded. HCC stage was classified according to the BCLC system, and interventions were categorized as curative or non-curative. International currencies were converted to US dollars using a currency converter<sup>[<xref ref-type="bibr" rid="B32">32</xref>]</sup>. No inflation adjustments were made to reported monetary values. Outcomes were assessed using three primary metrics: (1) QALYs and LYS as measures of clinical benefit; (2) incremental cost-effectiveness ratio (ICER) per QALY/LYS [or incremental cost-utility ratio (ICUR)] to show additional cost per unit benefit; and (3) ICER/willingness-to-pay (WTP) ratio to indicate cost-effectiveness, using WTP values reported in the studies or, when absent, the World Health Organization (WHO) guidance calculating WTP as three times the per capita gross domestic product (GDP)<sup>[<xref ref-type="bibr" rid="B33">33</xref>]</sup>. Data interpretation followed Sukhera<sup>[<xref ref-type="bibr" rid="B21">21</xref>]</sup>.</p>
        </sec>
      </sec>
      <sec id="sec2-2">
        <title>Evaluation of the risk of bias</title>
        <p>At least three investigators independently reviewed the included papers<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>. The risk of bias was first appraised using the Joanna Briggs Institute (JBI) checklist by three team members experienced in research quality assessment<sup>[<xref ref-type="bibr" rid="B88">88</xref>]</sup>. The JBI checklist comprises 11 items evaluating general and specific study attributes<sup>[<xref ref-type="bibr" rid="B88">88</xref>]</sup>. No minimum JBI score was required for inclusion; all studies meeting eligibility criteria were analyzed, though potential biases affecting cost-effectiveness outcomes were noted. Given that JBI does not cover all economic evaluation needs, we also assessed studies using the ECOBIAS checklist<sup>[<xref ref-type="bibr" rid="B89">89</xref>]</sup>.</p>
      </sec>
      <sec id="sec2-3">
        <title>Data description and analysis</title>
        <p>Clinical and demographic variables were described using reported means, standard deviations (SDs), medians, and percentages. Missing data were not imputed. Means were weighted across series when appropriate; medians were pooled via meta-analytic techniques when raw data were lacking, using a random-effects model with inverse-variance weighting to account for heterogeneity. Monetary values are those reported in the original articles; foreign currencies were converted to 2025 US dollars<sup>[<xref ref-type="bibr" rid="B32">32</xref>]</sup>. Data were tabulated (author, year, country assessed, treatments/comparators, QALYs/LYs, WTPs, and methodological notes) [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref>]<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>. For clarity and to mirror clinical practice, data were stratified by treatment type and number of active regimens (immunotherapy, multiple comparators, oral agents, second-line <italic>vs</italic>. placebo/BSC). A methodological summary combining JBI and ECOBIAS inputs appears in <xref ref-type="table" rid="t5">Tables 5</xref> and <xref ref-type="table" rid="t6">6</xref>.</p>
        <table-wrap id="t1">
          <label>Table 1</label>
          <caption>
            <p>Results of comparative economic studies on head-to-head comparisons of ICI as first-line therapy</p>
          </caption>
          <table frame="hsides" rules="groups" pdfpage="7">
            <thead>
              <tr>
                <td style="border-bottom:1;">
                  <bold>#</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Author<sup>[Ref.]</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Year</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Country</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Indication</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Treatments</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>QALY<sup>a</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>ICER<sup>b</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>WTP<sup>c</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>ICER/WTP<sup>d</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Remarks</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td colspan="11">Atezolizumab + Bevacizumab</td>
              </tr>
              <tr>
                <td>1</td>
                <td>Chang <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B34">34</xref>]</sup></td>
                <td>2025</td>
                <td>Taiwan</td>
                <td>aHCC</td>
                <td>ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>0.57</td>
                <td>US$117,000</td>
                <td>US$92,579.9</td>
                <td>1.2</td>
                <td>Data extracted from the IMBrave150 trial<break /><break />Partitioned survival analysis with a 20-year horizon<break /><break />The perspective was that of the National Health Insurance Administration<break /><break />Discount 0%-5%</td>
              </tr>
              <tr>
                <td>2</td>
                <td>Liu <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B35">35</xref>]</sup></td>
                <td>2025</td>
                <td>USA &amp; China</td>
                <td>aHCC</td>
                <td>ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>0.57 (USA)<break />0.47 (China)</td>
                <td>US$253,247.07 (USA)<break />US$181.552,71 (China)</td>
                <td>US$150,000 <break />(USA)<break />US$38,201.19 (China)</td>
                <td>1.68 (USA)<break />4.75 (China)</td>
                <td>Data extracted from the IMBrave150 trial<break /><break />Partitioned survival analysis with a life-time horizon<break /><break />Discount 3% in USA and 5% in China</td>
              </tr>
              <tr>
                <td>3</td>
                <td>Chee <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B36">36</xref>]</sup></td>
                <td>2024</td>
                <td>Singapore</td>
                <td>uHCC</td>
                <td>
                  <bold>ATE + BEVA</bold> <italic>vs</italic>. SORA</td>
                <td>1.09</td>
                <td>US$80,676.9</td>
                <td>US$89,432.5</td>
                <td>
                  <bold>0.9</bold>
                </td>
                <td>Data extracted from the IMBrave150 trial<break /><break />Partitioned survival model with a 10-year horizon</td>
              </tr>
              <tr>
                <td>4</td>
                <td>Sriphoosanaphan <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B37">37</xref>]</sup></td>
                <td>2024</td>
                <td>Thailand</td>
                <td>uHCC</td>
                <td>ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>0.8309</td>
                <td>US$54,589</td>
                <td>US$4,678</td>
                <td>11.66</td>
                <td>Data were extracted from a network meta-analysis of published studies<break /><break />Markov model with a life-time horizon<break /><break />Societal perspective<break /><break />Annual discount rate 3%</td>
              </tr>
              <tr>
                <td>5</td>
                <td>Tseng <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B38">38</xref>]</sup></td>
                <td>2023</td>
                <td>Taiwan</td>
                <td>uHCC</td>
                <td>
                  <bold>ATE + BEVA</bold> <italic>vs</italic>. SORA</td>
                <td>1.7</td>
                <td>US$75,192</td>
                <td>US$92,579.9</td>
                <td>
                  <bold>0.81</bold>
                </td>
                <td>Data were extracted from the IMBrave-105 trial<break /><break />Partitioned survival analysis with a 15-year horizon<break /><break />Annual discount rate %</td>
              </tr>
              <tr>
                <td>6</td>
                <td>Gaugain <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B39">39</xref>]</sup></td>
                <td>2023</td>
                <td>France</td>
                <td>a/uHCC</td>
                <td>
                  <bold>ATE + BEVA</bold> <italic>vs</italic>. SORA</td>
                <td>0.61</td>
                <td>€131,163<break />(i.e. US$155,352)</td>
                <td>€150,000 (US$177,663)</td>
                <td>
                  <bold>0.87</bold>
                </td>
                <td>Data were extracted from the French national real-world dataset and IMBrave150<break /><break />Partitioned survival model over a lifetime horizon</td>
              </tr>
              <tr>
                <td>7</td>
                <td>Li <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B40">40</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>a/uHCC</td>
                <td>
                  <bold>ATE + BEVA</bold> <italic>vs</italic>. NIV</td>
                <td>0.69<break />(1.13 LYS)</td>
                <td>US$113,892</td>
                <td>US$150,000<break /><break />Note: this WTP threshold is higher than what is used by most Chinese authors</td>
                <td>
                  <bold>0.75</bold>
                </td>
                <td>Data were extracted from a network meta-analysis integrating IMBrave150 and CheckMate459 trials<break /><break />Partitioned survival analysis with a 10-year horizon</td>
              </tr>
              <tr>
                <td>8</td>
                <td>Zhang <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B41">41</xref>]</sup></td>
                <td>2021</td>
                <td>China</td>
                <td>u/mHCC</td>
                <td>ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>0.484 <break />(0.623 LYS)</td>
                <td>US$322,500</td>
                <td>US$100,000-150,000</td>
                <td>3.22-2.15</td>
                <td>Data were extracted from the IMBrave105 trial<break /><break />Partitioned survival analysis with a 6-year horizon<break /><break />The US payor perspective was used</td>
              </tr>
              <tr>
                <td>9</td>
                <td>Chiang <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B42">42</xref>]</sup></td>
                <td>2021</td>
                <td>Hong Kong</td>
                <td>uHCC</td>
                <td>ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>0.44</td>
                <td>US$179,729</td>
                <td>US$100,000-150,000</td>
                <td>1.79-1.19<break /><break />Reducing the price of both drugs by 20% and 29% would satisfy the WTP thresholds (both scenarios)</td>
                <td>Data extracted from the IMBrave105 trial<break /><break />Markov model with a lifetime horizon<break /><break />US payor’s perspective</td>
              </tr>
              <tr>
                <td>10</td>
                <td>Su <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B43">43</xref>]</sup></td>
                <td>2021</td>
                <td>USA</td>
                <td>uHCC</td>
                <td>ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>0.530 <break />(1.297 LYS)</td>
                <td>US$169,223 (ICUR)</td>
                <td>US$150,000</td>
                <td>1.12<break /><break />Cost-effectiveness can be improved by reducing the cost of either drug and adapting schedules to patients’ risk factors</td>
                <td>Data extracted from the IMBrave105 trial and additional trials<break /><break />Partitioned survival analysis<break /><break />Annual discount rate 3%</td>
              </tr>
              <tr>
                <td>11</td>
                <td>Wen <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B44">44</xref>]</sup></td>
                <td>2021</td>
                <td>China</td>
                <td>uHCC</td>
                <td>ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>0.53</td>
                <td>US$145,546.21 (China)<break />US$168,030.21 (USA)</td>
                <td>US$28,527.00 (China)<break />US$150,000 (USA)</td>
                <td>5.1<break />1.12</td>
                <td>Data extracted from IMBrave105<break /><break />Markov model<break /><break />Chinese and US perspectives were considered</td>
              </tr>
              <tr>
                <td colspan="11">Sintilimab + Bevacizumab or Bevacizumab biosimilar</td>
              </tr>
              <tr>
                <td>12</td>
                <td>Xu <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B45">45</xref>]</sup></td>
                <td>2023</td>
                <td>China</td>
                <td>uHCC</td>
                <td>SIN + BEVAb<break />(IBI305)<sup>e</sup> <italic>vs</italic>. SORA</td>
                <td>0.33</td>
                <td>US$52,817.89</td>
                <td>US$38,334</td>
                <td>1.37</td>
                <td>Data were extracted from the ORIENT-32 trial<break /><break />Markov model<break /><break />Chinese payors perspective</td>
              </tr>
              <tr>
                <td>13</td>
                <td>Peng <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B46">46</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>uHCC</td>
                <td>
                  <bold>SIN + BEVAb</bold> <italic>vs</italic>. SORA</td>
                <td>1.27<break />(1.84 LYS)</td>
                <td>US$23,352</td>
                <td>US$30,552</td>
                <td>
                  <bold>0.76</bold>
                </td>
                <td>Data were extracted from the ORIENT-32 trial<break /><break />Markov model with a lifetime horizon<break /><break />Chinese healthcare system’s perspective</td>
              </tr>
              <tr>
                <td>14</td>
                <td>Zhou <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B47">47</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>u/mHCC</td>
                <td>
                  <bold>SIN + BEVAb</bold> <italic>vs</italic>. LEN</td>
                <td>0.493</td>
                <td>US$24,462</td>
                <td>US$12,516<break />(low-income areas)<break />US$37,547<break />(national average)</td>
                <td>1.9<break /><break /><bold>0.65</bold><break /><break />The cost-effectiveness ratio was particularly sensitive to the cost of biosimilar BEVA</td>
                <td>Data were extracted from ORIENT-32 and REFLECT trials<break /><break />Partitioned survival analysis with a lifetime horizon<break /><break />Chinese healthcare system perspective</td>
              </tr>
              <tr>
                <td>15</td>
                <td>Zhou <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B48">48</xref>]</sup></td>
                <td>2021</td>
                <td>China</td>
                <td>uHCC<break /></td>
                <td>
                  <bold>SIN + BEVA</bold> <italic>vs</italic>. SORA</td>
                <td>0.5</td>
                <td>US$20,968</td>
                <td>US$33,592</td>
                <td>
                  <bold>0.62</bold>
                  <break />
                  <break />Cost-effectiveness may further increase by reducing the dosage of BEVA to 7.5 mg/kg</td>
                <td>Data were extracted from the ORIENT-32 trial<break /><break />Partitioned survival analysis with a lifetime horizon<break /><break />Chinese healthcare system’s perspective</td>
              </tr>
              <tr>
                <td colspan="11">STRIDE (Single dose tremelimumab and regular interval durvalumab)</td>
              </tr>
              <tr>
                <td>16</td>
                <td>Cheng <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B49">49</xref>]</sup></td>
                <td>2025</td>
                <td>USA</td>
                <td>uHCC</td>
                <td>
                  <bold>TREM + DUR (STRIDE)</bold> <italic>vs</italic>. SORA</td>
                <td>0.57</td>
                <td>US$19,239</td>
                <td>US$150,000</td>
                <td>
                  <bold>0.13</bold>
                </td>
                <td>Data extracted from the HIMALAYA trial and network meta-analysis of published trials<break /><break />Partitioned survival analysis with a 20-year horizon<break /><break />Payer perspective</td>
              </tr>
              <tr>
                <td>17</td>
                <td>Xiong <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B50">50</xref>]</sup></td>
                <td>2024</td>
                <td>USA</td>
                <td>uHCC</td>
                <td>1. <bold>TREM + DUR (STRIDE)</bold><break />2. DUR alone <break /><italic>vs</italic>. SORA</td>
                <td>0.2 (0.27 LYS)<break /><break />0.08 (0.15 LYS)</td>
                <td>1.US$97,995.5 (STRIDE <break /><italic>vs</italic>. SORA)<break />2.US$754,408 (STRIDE<break /><italic>vs</italic>. DUR alone)</td>
                <td>US$150.000</td>
                <td>
                  <bold>0.65</bold>
                  <break />
                  <break />5.02</td>
                <td>Data extracted from the HIMALAYA protocol and STRIDE strategy<break /><break />Partitioned survival analysis with a 48-month horizon<break /><break />US societal perspective</td>
              </tr>
              <tr>
                <td>18</td>
                <td>Liao <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B51">51</xref>]</sup></td>
                <td>2024</td>
                <td>China</td>
                <td>uHCC<break />High AFP</td>
                <td>
                  <bold>TREM + DUR (STRIDE)</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.29</td>
                <td>US$72,762</td>
                <td>US$150.000</td>
                <td>
                  <bold>0.48</bold>
                </td>
                <td>Data extracted from the HIMALAYA protocol and STRIDE strategy<break /><break />Markov model</td>
              </tr>
              <tr>
                <td colspan="11">Camrelizumab + Rivoceranib</td>
              </tr>
              <tr>
                <td>19</td>
                <td>Zhao <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B52">52</xref>]</sup></td>
                <td>2024</td>
                <td>China</td>
                <td>uHCC</td>
                <td>
                  <bold>CAM + RIV</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.80</td>
                <td>US$9,150.75</td>
                <td>US$16,426.80<break />(low-income regions)<break />US$34,319.01<break />(medium-income regions)<break />US$81,036.63<break />(high-income regions)</td>
                <td>
                  <bold>0.56</bold>
                  <break />
                  <break />
                  <bold>0.27</bold>
                  <break />
                  <break />
                  <bold>0.11</bold>
                </td>
                <td>Data extracted from the CARES-310 trial<break /><break />Markov state transition model<break /><break />Sensitivity analysis stratified based on regions income</td>
              </tr>
              <tr>
                <td>20</td>
                <td>Wei <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B53">53</xref>]</sup></td>
                <td>2024</td>
                <td>USA &amp; China</td>
                <td>uHCC</td>
                <td>
                  <bold>CAM + RIV</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.71 (USA)<break />0.64 (China)</td>
                <td>US$122,388.62 (USA)<break />US$30,410.56 (China)</td>
                <td>US$100.000-150.000,00<break />(USA)<break />US$23,932.5-35,898.8<break />(China)</td>
                <td>1.22-<bold>0.81</bold><break /><break />1.27-<bold>0.84</bold></td>
                <td>Data extracted from the CARES-310 trial<break /><break />USA and Chinese payors perspective<break /><break />Partitioned survival model with a 15-year time horizon</td>
              </tr>
              <tr>
                <td colspan="11">Tislelizumab</td>
              </tr>
              <tr>
                <td>21</td>
                <td>Sun <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B54">54</xref>]</sup></td>
                <td>2024</td>
                <td>China<break />USA<break />Europe</td>
                <td>uHCC</td>
                <td>
                  <bold>TIS</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.56 (USA and Europe)<break />0.52 (China)</td>
                <td>US$108,812.5 (USA)<break />US$94,880.40 (Europe)<break />(Europe)<break />US$14,206.80 (China)</td>
                <td>US$150.000(USA)<break />US$100.000(Europe)<break />US$38,186 (China)</td>
                <td>
                  <bold>0.72</bold>
                  <break />
                  <bold>0.94</bold>
                  <break />
                  <bold>0.37</bold>
                </td>
                <td>Data extracted from the RATIONALE-301 trial<break /><break />Partitioned survival model<break /><break />Monte Carlo simulation</td>
              </tr>
              <tr>
                <td>22</td>
                <td>Zheng <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B55">55</xref>]</sup></td>
                <td>2024</td>
                <td>China</td>
                <td>uHCC</td>
                <td>
                  <bold>TIS</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.18</td>
                <td>US$10413.17</td>
                <td>US$37,304.34</td>
                <td>
                  <bold>0.27</bold>
                </td>
                <td>Data extracted from the RATIONALE-301 trial<break /><break />Partitioned survival model with a 10-year survival horizon</td>
              </tr>
              <tr>
                <td>23</td>
                <td>Chen <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B56">56</xref>]</sup></td>
                <td>2024</td>
                <td>China</td>
                <td>uHCC</td>
                <td>
                  <bold>TIS</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.568</td>
                <td>US$ 22,869.64</td>
                <td>$37,653</td>
                <td>
                  <bold>0.60</bold>
                </td>
                <td>Data extracted from the RATIONALE-301 trial<break /><break />Partitioned survival model with a lifetime horizon<break /><break />National Health Service perspective</td>
              </tr>
              <tr>
                <td colspan="11">Nivolumab</td>
              </tr>
              <tr>
                <td>24</td>
                <td>Shu <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B57">57</xref>]</sup></td>
                <td>2023</td>
                <td>China</td>
                <td>aHCC</td>
                <td>NIV <italic>vs</italic>. SORA<break /></td>
                <td>0.27</td>
                <td>US$236,765.93</td>
                <td>US$38,201.1</td>
                <td>6.19</td>
                <td>Data were extracted from the CheckMate-459 trial<break /><break />Partitioned survival model<break /><break />Chinese healthcare system perspective</td>
              </tr>
              <tr>
                <td>25</td>
                <td>Li <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B58">58</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>aHCC</td>
                <td>NIV <italic>vs</italic>. SORA<break /></td>
                <td>0.32<break />(0.50 LYS)</td>
                <td>US$220,864</td>
                <td>US$150,000<break /><break />Note: this WTP threshold is higher than what is used by most Chinese authors</td>
                <td>1.47<break /><break />However, cost-effectiveness increases for BCLC-B patients</td>
                <td>Data were extracted from CheckMate459 trial<break /><break />Partitioned survival analysis with a 10-year lifetime horizon</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p><sup>a</sup>QALY is expressed as an increase or decrease versus the comparator; <sup>b</sup>ICER is expressed per QALY unit; <sup>c</sup>WTP is expressed per QALY unit; <sup>d</sup>If ICER/WTP &gt; 1, the treatment is not cost-effective in the context explored; <sup>e</sup>IBI305 is a bevacizumab biosimilar. Cost-effective treatments are highlighted in bold. QALY: Quality-adjusted life year; ICER: incremental cost-effectiveness ratio; WTP: willingness to pay; ICI: immune checkpoint inhibitor; aHCC: advanced hepatocellular carcinoma; uHCC: unresectable hepatocellular carcinoma; mHCC: metastatic hepatocellular carcinoma; ATE: atezolizumab; BEVA: bevacizumab; SORA: sorafenib; NIV: nivolumab; LYS: life-years saved; HCC: hepatocellular carcinoma; SEER: Surveillance, Epidemiology, and End Results; ICUR: incremental cost-utility ratio; SIN: sintilimab; BEVAb: bevacizumab biosimilar; LEN: lenvatinib; STRIDE: single tremelimumab regular interval durvalumab; TREM: tremelimumab; DUR: durvalumab; HCV: hepatitis C virus; AFP: alpha-fetoprotein; CAM: camrelizumab; RIV: rivoceranib; TIS: tislelizumab; BCLC: Barcelona Clinic Liver Cancer.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap id="t2">
          <label>Table 2</label>
          <caption>
            <p>Results of economic studies comparing simultaneously multiple ICI- and TKI/VEGFi-based regimens as first-line therapy irrespective of the used comparator(s)</p>
          </caption>
          <table frame="hsides" rules="groups" pdfpage="11">
            <tbody>
              <tr>
                <td>
                  <bold>#</bold>
                </td>
                <td>
                  <bold>Author</bold>
                </td>
                <td>
                  <bold>Year</bold>
                </td>
                <td>
                  <bold>Country</bold>
                </td>
                <td>
                  <bold>Indication</bold>
                </td>
                <td>
                  <bold>Treatments</bold>
                </td>
                <td>
                  <bold>QALY<sup>a</sup></bold>
                </td>
                <td>
                  <bold>ICER<sup>b</sup></bold>
                </td>
                <td>
                  <bold>WTP<sup>c</sup></bold>
                </td>
                <td>
                  <bold>ICER/WTP<sup>d</sup></bold>
                </td>
                <td>
                  <bold>Remarks</bold>
                </td>
              </tr>
              <tr>
                <td colspan="11">Sequencing treatments</td>
              </tr>
              <tr>
                <td>26</td>
                <td>Sherrow <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup></td>
                <td>2020</td>
                <td>USA</td>
                <td>uHCC<break />1st and 2nd-line treatment</td>
                <td>8 different 1st- and 2nd-line sequences using:<break />SORA, REGO, CABO, PEM, NIV, LEN<break />(SORA-REGO; SORA-CABO;<break />SORA-NIV;<break /><bold>SORA-PEM</bold>;<break />LEN-REGO;<break />LEN-CABO;<break />LEN-NIV;<break /><bold>LEN-PEM</bold>)</td>
                <td>Not applicable due to multiple comparators</td>
                <td>The strategies with the highest cost-effectiveness were TKI followed by ICI<break /><break />The 2 most cost-effective strategies were:<break />SORA-PEM (US$227,741.03)<break />LEN-PEM<break />(US$230,371.17)</td>
                <td>US$150,000-300,000</td>
                <td>A sequencing strategy of 1st-line TKI followed by 2nd-line ICI is more cost-effective than TKI-TKI<break /><break />SORA-PEM and LEN-PEM are the most cost-effective but well above the WTP threshold of US$150,000</td>
                <td>Data extracted from RCT on all drugs included in the study<break /><break />Markov model with 9 possible states</td>
              </tr>
              <tr>
                <td colspan="11">Multiple regimens comparisons</td>
              </tr>
              <tr>
                <td>27</td>
                <td>Lian <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B60">60</xref>]</sup></td>
                <td>2024</td>
                <td>China<break />USA</td>
                <td>uHCC</td>
                <td>1. ATE + BEVA;<break />2. TREM + DUR (STRIDE);<break />3. <bold>DUR</bold>;<break />4. LEN <italic>vs</italic>. SORA</td>
                <td>1. 1.92<break />(2.73 LYS)<break />2. 1.67<break />(2.40 LYS)<break />3. 1.52<break />(2.18)<break />4. 1.406<break />(2.05 LYS)</td>
                <td>1. US$196,704<break />2. US$800,755<break />3. Reported as dominant due to lower cost than SORA (US$178,200 <italic>vs</italic>. 202,831)<break />4. US$2,032,756</td>
                <td>US$150.000,00</td>
                <td>1. 1.31<break />2. 5.33<break />3. <bold>Dominant</bold><break />4. 13.55</td>
                <td>Data extracted from literatures studies and network meta-analysis<break /><break />Partitioned survival analysis with a 10-year horizon<break /><break />US healthcare and societal perspectives</td>
              </tr>
              <tr>
                <td>28</td>
                <td>Wen <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup></td>
                <td>2024</td>
                <td>China</td>
                <td>uHCC</td>
                <td>1. TREM + DUR (STRIDE);<break />2. ATE + BEVA;<break />3. <bold>SIN + BEVAb</bold>;<break />4. <bold>CAM + RIV</bold>;<break />5. PEM + LEN</td>
                <td>1 = 0.73<break /><break />2 = 0.90<break />3 = 1.12<break />4 = 0.91<break />5 = 0.83</td>
                <td>1. US$115,887.68<break /><break />2. US$78,872.289<break />3. US$24,072.86<break />4. US$13,306.89<break />5. US$66,725.94</td>
                <td>US$35,526.9</td>
                <td>3.2<break /><break />2.2<break /><bold>0.67</bold><break /><bold>0.37</bold><break />1.87</td>
                <td>Data extracted from HIMALAYA, IMBrave150, ORIENT-32, CARES-310, and LEAP-002 trials<break /><break />Markov model with a 10-year horizon<break /><break />Monte Carlo simulations</td>
              </tr>
              <tr>
                <td>29</td>
                <td>Sun <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B62">62</xref>]</sup></td>
                <td>2022</td>
                <td>China, USA</td>
                <td>aHCC</td>
                <td>(China)<break />1. ATE + BEVA<break />2. SIN + BEVA<break />3. <bold>LEN</bold><break />4. DONA<break />5. SORA<break /><break />(USA)<break />1. <bold>ATE + BEVA</bold><break />2. <bold>LEN</bold><break />3. NIV<break />4. SORA</td>
                <td>(China)<break />Compared with DONA<break />1. 0.46<break />2. 1.25<break />3. 0.77<break />4. -1.08<break /><break />(USA)<break />Compared with NIV<break />1. 3.76<break />2. 4.29<break />3. 1.92</td>
                <td>(China)<break />Compared with DONA<break />1. US$85,607.88<break />2. US$12,109.27<break />3. US$1,651.47<break /><break />(USA)<break />Compared with NIV<break />1. 47,896.93<break />2. 25,022.13<break />3. 89,972.04</td>
                <td>US$11,101.70 (China)<break />US$69,375.0 (USA)<break /><break />NOTE: the WTP thresholds are lower than what is reported by other authors and correspond to the lowest range of WHO’s recommendations</td>
                <td>(China)<break />Compared to DONA<break />1. 7.71<break />2. 1.09<break />3. <bold>0.14</bold><break /><break />(USA)<break />Compared to NIV<break />1. <bold>0.69</bold><break />2. <bold>0.36</bold><break />3. 1.29</td>
                <td>Network meta-analysis based on RCTs<break /><break />Markov model<break /><break />Annual discount rate 0%-8% in China and 0%-5% in USA</td>
              </tr>
              <tr>
                <td>30</td>
                <td>Li <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B63">63</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>uHCC</td>
                <td>1. SIN + BEVAb<break />2. ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>1. 0.617<break />2. 0.596</td>
                <td>1. US$39,766.86<break />2. US$103,037.66</td>
                <td>US$33,500</td>
                <td>1. 1.18<break />2. 3.07<break /><break />SIN + BEVAb cost-effectiveness is favorable in the context of a patient-assisted program scenario</td>
                <td>Data were extracted from IMBrave150 and ORIENT-32 trials<break /><break />Partitioned survival model with a 15-year lifetime horizon<break /><break />Annual discount rates 5%<break /><break />A patience-assisted program was included in sensitivity analysis</td>
              </tr>
              <tr>
                <td>31</td>
                <td>Gong <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B64">64</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>aHCC</td>
                <td>1. LEN<break />2. ATE + BEVA<break />3. SIN + IBI305<sup>e</sup><break /><italic>vs</italic>. SORA</td>
                <td>1. 0.04<break />2. 0.31<break />3. 0.87</td>
                <td>1. US$188.625<break />2. US$75,150.3<break />3. US$144,513</td>
                <td>US$36,600</td>
                <td>1. 5.15<break />2. 2.05<break />3. 3.94</td>
                <td>Data were extracted from previous trials (NCT01761266, NCT0343437, NCT03794440)<break /><break />Partitioned survival model<break /><break />Interviews with clinicians were used to derive costs<break /><break />Annual discount rate of 5%</td>
              </tr>
              <tr>
                <td>32</td>
                <td>Wang <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>aHCC</td>
                <td>1. <bold>SUN</bold><break />2. LEN<break />3. DONA<break />4. SORA + ERL<break />5. SIN + IBI305<sup>e</sup><break />6. LIN<break />7. BRIVA<break />8. ATE + BEVA <italic>vs</italic>. SORA</td>
                <td>1. 0.78<break />2. 0.45<break />3. 0.83<break />4. 0.81<break />5. 0.82<break />6. 0.82<break />7. 0.85<break />8. 0.85</td>
                <td>1. US$551<break />2. US$121,059<break />3. US$68,869<break />4. US$95,545<break />5. US$115,760<break />6. US$128,527<break />7. US$115,760<break />8. US$160,049</td>
                <td>US$37,654.5</td>
                <td>1. <bold>0.01</bold><break />2. 3.21<break />3. 1.82<break />4. 2.53<break />5. 3.07<break />6. 3.41<break />7. 3.07<break />8. 4.2</td>
                <td>A theoretical model for first-line therapies was constructed based on SHARP and NCT00492752 trials<break /><break />Markov model with a 10-year time horizon<break /><break />Chinese payors perspective and only direct costs included</td>
              </tr>
              <tr>
                <td>33</td>
                <td>Guan <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B66">66</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>uHCC</td>
                <td>1. DONA<break />2. SORA<break />3. LEN</td>
                <td>1. 1.106<break />(1.755 LYS)<break />2. 0.999<break />(1.577 LYS)<break />3. 0.915<break />(1.410 LYS)<break /><break />DONA <italic>vs</italic>. LEN = 0.107 (0.178 LYS)<break />DONA <italic>vs</italic>. SORA = 0.191<break />(0.345 LYS)<break />LEN <italic>vs</italic>. SORA = 0.0084 (0,167 LYS)</td>
                <td>1. US$42,116<break />2. U$44,261<break />3. US$43,193<break /><break />Only costs were provided and ICER was generically indicated to be dominated by DONA</td>
                <td>U$31,315</td>
                <td>1. 1.34<break />2. 1.41<break />3. 1.37</td>
                <td>Data were extracted from network meta-analysis using ZGDH-3 phase 2 and 3 trials and REFLECT trial<break /><break />Partitioned survival analysis with a lifetime horizon</td>
              </tr>
              <tr>
                <td>34</td>
                <td>Zhao <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B67">67</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>uHCC</td>
                <td>1. SORA<break />2. LEN<break />3. <bold>DONA</bold><break />4. SIN + BEVAb<break />5. ATE + BEVA</td>
                <td>Compared to SORA:<break />LEN = 0.16 (0.25 LYS)<break />DONA = 0.19 (0.30 LYS)<break />SIN + BEVAb = 0.51 (0.95 LYS)<break />ATE + BEVA = 0.86 (1.46 LYS)</td>
                <td>Compared to SORA:<break />LEN = US$40,667.92<break />DONA = US$27,630.63<break />SIN + BEVAb = US$51,877.36<break />ATE + BEVA = US$130,508.44</td>
                <td>US$33,521</td>
                <td>LEN = 1.21<break /><bold>DONA = 0.82</bold><break />SIN + BEVAb = 1.54<break />ATE + BEVA = 3.89</td>
                <td>Network meta-analysis of 4 trials (IMBrave105, REFLECT, ORIENT-32, ZGDH-3)<break /><break />Partitioned survival analysis<break /><break />Chinese healthcare system’s perspective</td>
              </tr>
              <tr>
                <td>35</td>
                <td>Giuliani <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B68">68</xref>]</sup></td>
                <td>2021</td>
                <td>Italy</td>
                <td>aHCC</td>
                <td>1. LEN<break />2. ATE + BEVA<break /><italic>vs</italic>. SORA</td>
                <td>Not reported</td>
                <td>€139.24 (per month of PFS)<break />€9198.82 (per month of PFS)</td>
                <td>Not reported</td>
                <td>Not reported</td>
                <td>Data were extracted from the IMBrave105 and REFLECT trials<break /><break />Survival model not clearly indicated<break /><break />PFS rather than overall survival was used to compute ICER<break /><break />Perspective of a National Health System hospital facility</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p><sup>QALY</sup> is expressed as an increase or decrease versus the comparator; <sup>b</sup>ICER is expressed per QALY unit; <sup>c</sup>WTP is expressed per QALY unit; <sup>d</sup>If ICER/WTP &gt; 1, the treatment is not cost-effective in the context explored; <sup>e</sup>IBI305 is a bevacizumab biosimilar. Cost-effective treatments are indicated in bold. QALY: Quality-adjusted life year; ICER: incremental cost-effectiveness ratio; WTP: willingness to pay; ICI: immune checkpoint inhibitor; TKI: tyrosine kinase inhibitor; VEGFi: vascular endothelial growth factor inhibitors or antagonists; uHCC: unresectable hepatocellular carcinoma; aHCC: advanced hepatocellular carcinoma; SORA: sorafenib; REGO: regorafenib; CABO: cabozantinib; PEM: pembrolizumab; NIV: nivolumab; LEN: lenvatinib; RCT: randomized controlled trial; ATE: atezolizumab; BEVA: bevacizumab; TREM: tremelimumab; DUR: durvalumab; STRIDE: single tremelimumab regular interval durvalumab; LYS: life-years saved; SIN: sintilimab; BEVAb: bevacizumab biosimilar; CAM: camrelizumab; RIV: rivoceranib; DONA: donafenib; WHO: World Health Organization; IBI305: bevacizumab biosimilar IBI305; SUN: sunitinib; ERL: erlotinib; LIN: linifanib; BRIVA: brivanib; PFS: progression-free survival; ICUR: incremental cost-utility ratio.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap id="t3">
          <label>Table 3</label>
          <caption>
            <p>Results of economic studies on head-to-head comparison of TKI/VEGFi-based regimens only as first-line therapy irrespective of the used comparator(s)</p>
          </caption>
          <table frame="hsides" rules="groups" pdfpage="14">
            <thead>
              <tr>
                <td style="border-bottom:1;">
                  <bold>#</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Author</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Year</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Country</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Indication</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Treatments</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>QALY<sup>a</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>ICER<sup>b</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>WTP<sup>c</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>ICER/WTP<sup>d</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Remarks</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td colspan="11">TKI/VEGFi</td>
              </tr>
              <tr>
                <td>36</td>
                <td>Meng <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B69">69</xref>]</sup></td>
                <td>2022</td>
                <td>China</td>
                <td>u/mHCC</td>
                <td>DONA <italic>vs</italic>. <bold>SORA</bold></td>
                <td>0.184</td>
                <td>US$41,081.52<break />US$13,439.10 (if the branded price of SORA was considered)</td>
                <td>USS$10,499.74<break /><bold>TKI/VEGFi</bold><break /><bold>TKI/VEGFi</bold><break /><break />31,499.23</td>
                <td>3.9-1.3<break />1.2-<bold>0.42</bold> (if a reduced DONA price is considered)</td>
                <td>Data were extracted from network using ZGDH-3 phase 2 and 3 trials<break /><break />Partitioned survival analysis with a lifetime horizon<break /><break />Chinese healthcare system’s perspective<break /><break />Annual discount rates 5%<break /><break />Scenario analysis with the brand and generic price of SORA</td>
              </tr>
              <tr>
                <td>37</td>
                <td>Meyers <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B70">70</xref>]</sup></td>
                <td>2021</td>
                <td>Canada</td>
                <td>uHCC</td>
                <td>
                  <bold>LEN</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.17 (0.22 LYS)</td>
                <td>-US$5021 (as ICUR)</td>
                <td>Not reported</td>
                <td>LEN is dominant on SORA due to its reduced cost</td>
                <td>Data extracted from the REFLECT trial<break /><break />Partitioned survival analysis over a 10-year horizon<break /><break />Canadian health provider’s perspective</td>
              </tr>
              <tr>
                <td>38</td>
                <td>Ikeda <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B71">71</xref>]</sup></td>
                <td>2021</td>
                <td>Japan</td>
                <td>uHCC</td>
                <td>
                  <bold>LEN</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.31</td>
                <td>-JPY156799 (US$1060,15)</td>
                <td>Not reported</td>
                <td>LEN dominates on SORA due to reduced costs and improved QALY</td>
                <td>Data extracted from the Japanese population of the REFLECT trial<break /><break />Partitioned survival model with a lifetime horizon<break /><break />Japanese healthcare system’s perspective<break /><break />Annual discount rate of 2%</td>
              </tr>
              <tr>
                <td>39</td>
                <td>Saiyed <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B72">72</xref>]</sup></td>
                <td>2020</td>
                <td>Australia</td>
                <td>uHCC</td>
                <td>
                  <bold>LEN</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.119</td>
                <td>A$33,028 (US$21,792.3)</td>
                <td>AU$50,000 (US$32,990.7)</td>
                <td>
                  <bold>0.66</bold>
                </td>
                <td>Data extracted from the REFLECT trial<break /><break />Partitioned survival model with a 10-year horizon<break /><break />A health-system perspective was adopted</td>
              </tr>
              <tr>
                <td>40</td>
                <td>Cai <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B73">73</xref>]</sup></td>
                <td>2020</td>
                <td>China</td>
                <td>uHCC</td>
                <td>
                  <bold>LEN</bold><break /><italic>vs</italic>. SORA</td>
                <td>1.122 (&lt; 60 kg)<break />1.122 ( 60 kg)</td>
                <td>US$11,825.94 (&lt; 60 kg)<break />US$28,627.12 ( 60 kg)</td>
                <td>US$29,306.37</td>
                <td>
                  <bold>0.40</bold>
                  <break />
                  <bold>0.97</bold>
                </td>
                <td>Data extracted from the REFLECT trial Chinese patients<break /><break />Markov model with transition states<break /><break />Annual discount rate 3%<break /><break />The China National Healthcare Medical Administration perspective was used</td>
              </tr>
              <tr>
                <td>41</td>
                <td>Kim <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B74">74</xref>]</sup></td>
                <td>2020</td>
                <td>Canada</td>
                <td>aHCC</td>
                <td>
                  <bold>LEN</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.132</td>
                <td>In the full-price SORA scenario, LEN dominated on SORA and was associated with a 23,719.34US$ cost saving<break /><break />In the 90%-discount SORA scenario, LEN ICER was US$104,668.71</td>
                <td>US$0-50,000</td>
                <td>LEN is cost-saving as compared to SORA and its cost-effectiveness is well below the WTP threshold in the full-price SORA scenario<break /><break />However, introduction of a generic SORA formulation or SORA discounted price might reduce LEN cost savings</td>
                <td>Data extracted from the REFLECT trial<break /><break />State-transition model with a 5-year horizon<break /><break />Annual discount rate 1.5%<break /><break />Different scenarios were considered based on SORA discount rates (20%-90% discount rate)</td>
              </tr>
              <tr>
                <td>42</td>
                <td>Kobayashi <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B75">75</xref>]</sup></td>
                <td>2019</td>
                <td>Japan</td>
                <td>uHCC</td>
                <td>
                  <bold>LEN</bold><break /><italic>vs</italic>. SORA</td>
                <td>0.23 (0.27 LYS)</td>
                <td>-JPY406,307 (US$2,745.67)</td>
                <td>JPY5,000,000 (US$33,788.1)</td>
                <td>LEN is associated with cost savings <italic>vs</italic>. SORA and improved QALY</td>
                <td>Data were extracted from the REFLECT trial<break /><break />Partitioned survival analysis with a lifetime horizon</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p><sup>a</sup>QALY is expressed as an increase or decrease versus the comparator; <sup>b</sup>ICER is expressed per QALY unit; <sup>c</sup>WTP is expressed per QALY unit; <sup>d</sup>If ICER/WTP &gt; 1, the treatment is not cost-effective in the context explored; <sup>e</sup>IBI305 is a bevacizumab biosimilar. Cost-effective treatments are indicated in bold. TKI: Tyrosine kinase inhibitor; VEGFi: vascular endothelial growth factor inhibitors or antagonists; uHCC: unresectable hepatocellular carcinoma; mHCC: metastatic hepatocellular carcinoma; aHCC: advanced hepatocellular carcinoma; DONA: donafenib; SORA: sorafenib; QALY: quality-adjusted life year; ICER: incremental cost-effectiveness ratio; WTP: willingness to pay; LEN: lenvatinib; LYS: life-years saved; ICUR: incremental cost-utility ratio; JPY: Japanese yen.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap id="t4">
          <label>Table 4</label>
          <caption>
            <p>Results of comparative economic studies on first- or second-line therapies with placebo and/or BSC as the comparator</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td style="border-bottom:1;">
                  <bold>#</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Author</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Year</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Country</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Indication</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Treatments</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>QALY<sup>a</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>ICER<sup>b</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>WTP<sup>c</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>ICER/WTP<sup>d</sup></bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Remarks</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td colspan="11">Second-line cabozantinib</td>
              </tr>
              <tr>
                <td>43</td>
                <td>Sieg <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B76">76</xref>]</sup></td>
                <td>2020</td>
                <td>Germany<break />USA</td>
                <td>aHCC second-line treatment</td>
                <td>CABO <italic>vs</italic>. BSC</td>
                <td>0.15 (0.18 LYS)</td>
                <td>US$375,470 (Germany)<break />US$1,189,796 (US pricing)</td>
                <td>US$163,371 (Germany)<break />US$150,000 (USA)</td>
                <td>2.29<break />7.93</td>
                <td>Data extracted from the CELESTIAL trial<break /><break />Markov model with a lifetime horizon<break /><break />German statutory health insurance perspective compared with the US scenario and prices</td>
              </tr>
              <tr>
                <td>44</td>
                <td>Shlomai <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B77">77</xref>]</sup></td>
                <td>2019</td>
                <td>Israel</td>
                <td>aHCC second-line treatment</td>
                <td>CABO <italic>vs</italic>. placebo</td>
                <td>0.16 (0.22 LYS)</td>
                <td>US$469,374</td>
                <td>US$230,000</td>
                <td>2.04</td>
                <td>Data extracted from the CELESTIAL trial<break /><break />Markov model with a 5-year time horizon<break /><break />National health system perspective</td>
              </tr>
              <tr>
                <td>45</td>
                <td>Liao <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B78">78</xref>]</sup></td>
                <td>2019</td>
                <td>China</td>
                <td>aHCC second-line treatment</td>
                <td>CABO <italic>vs</italic>. placebo</td>
                <td>0.13</td>
                <td>US$833,497 (USA)<break />US$304,177 (UK)<break />US$156,437 (China)</td>
                <td>US$150,000 (USA)<break />US$76,671 (UK)<break />US$26,481 (China)</td>
                <td>5.55<break />3.96<break />5.91</td>
                <td>Data extracted from the CELESTIAL trial<break /><break />Markov model with a 10-year horizon<break /><break />China, US and UK payors’ perspectives were used</td>
              </tr>
              <tr>
                <td>46</td>
                <td>Soto-Perez-de-Celis <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B79">79</xref>]</sup></td>
                <td>2019</td>
                <td>Brazil</td>
                <td>aHCC second-line treatment</td>
                <td>CABO <italic>vs</italic>. placebo</td>
                <td>0.067</td>
                <td>US$1,040,675</td>
                <td>US$100,000</td>
                <td>10.41</td>
                <td>Data extracted from the CELESTIAL trial<break /><break />Decision-analytic model with 3 mutually exclusive health states<break /><break />US healthcare system’s perspective</td>
              </tr>
              <tr>
                <td colspan="11">Second-line regorafenib</td>
              </tr>
              <tr>
                <td>47</td>
                <td>Shlomai <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B80">80</xref>]</sup></td>
                <td>2018</td>
                <td>Israel</td>
                <td>uHCC<break />second-line treatment after SORA</td>
                <td>REGO + BSC <italic>vs</italic>. placebo + BSC</td>
                <td>0.25 (0.38 LYS)</td>
                <td>US$201,797-268,506</td>
                <td>US$150,000</td>
                <td>1.34-1.79</td>
                <td>Data extracted from the RESORCE trial<break /><break />Markov model<break /><break />Annual discount rate 3%</td>
              </tr>
              <tr>
                <td>48</td>
                <td>Parikh <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B81">81</xref>]</sup></td>
                <td>2017</td>
                <td>USA</td>
                <td>aHCC</td>
                <td>REGO <italic>vs</italic>. BSC</td>
                <td>0.18</td>
                <td>US$224,362</td>
                <td>US$100,000</td>
                <td>2.24<break /><break />Reducing REGO price would increase acceptability</td>
                <td>Data extracted from RESORCE trial<break /><break />Markov model<break /><break />US healthcare perspective</td>
              </tr>
              <tr>
                <td colspan="11">Second-line pembrolizumab</td>
              </tr>
              <tr>
                <td>49</td>
                <td>Chiang <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B82">82</xref>]</sup></td>
                <td>2021</td>
                <td>China</td>
                <td>uHCC<break />second line after SORA</td>
                <td>PEM <italic>vs</italic>. placebo (both with BSC)</td>
                <td>0.138</td>
                <td>US$340,409</td>
                <td>US$150,000<break /><break />NOTE: the authors used the US national WTP</td>
                <td>2.26<break /><break />The model was sensitive to cost of PEM, OS, PFS, and health utility of placebo</td>
                <td>Data extracted from the KEYNOTE-240 trial. Quality measures were extracted from a bladder cancer trial. Health utility measures of placebo were extracted from the RESORCE trial (regorafenib <italic>vs</italic>. placebo as second line therapy)<break /><break />Markov model with a lifetime horizon</td>
              </tr>
              <tr>
                <td colspan="11">Second-line ramucirumab</td>
              </tr>
              <tr>
                <td>50</td>
                <td>Zheng <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B83">83</xref>]</sup></td>
                <td>2019</td>
                <td>China</td>
                <td>aHCC<break />second- line treatment</td>
                <td>RAMU <italic>vs</italic>. placebo in patients with AFP  400 ng/mL</td>
                <td>0.07</td>
                <td>US$782,104.57</td>
                <td>US$100,000<break /><break />NOTE: the authors used a WTP threshold different than 3 times the per capita GDP</td>
                <td>7.82</td>
                <td>Data extracted from the REACH-2 trial<break /><break />Markov model and a 10-year horizon<break /><break />USA payors’ perspective</td>
              </tr>
              <tr>
                <td colspan="11">First-line sorafenib <italic>vs</italic>. placebo/BSC</td>
              </tr>
              <tr>
                <td>51</td>
                <td>Gupta <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B84">84</xref>]</sup></td>
                <td>2018</td>
                <td>India</td>
                <td>aHCC</td>
                <td>SORA <italic>vs</italic>. placebo</td>
                <td>0.19 (0.25 LYS)</td>
                <td>US$7861</td>
                <td>Not reported</td>
                <td>SORA cost-effectiveness is 4.2 higher than GDP</td>
                <td>Data were extracted from the Asia-Pacific SORA trial<break /><break />Markov model with a lifetime horizon<break /><break />Societal perspective</td>
              </tr>
              <tr>
                <td>52<break /></td>
                <td>Hamdy Elsisi <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B85">85</xref>]</sup></td>
                <td>2018</td>
                <td>Egypt</td>
                <td>aHCC</td>
                <td>SORA <italic>vs</italic>. placebo</td>
                <td>3.96</td>
                <td>US$286,776</td>
                <td>US$41,372</td>
                <td>6.9</td>
                <td>Data extracted from the SHARP trial<break /><break />Markov model with a 4-year horizon</td>
              </tr>
              <tr>
                <td>53</td>
                <td>Parikh <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B86">86</xref>]</sup></td>
                <td>2017</td>
                <td>USA</td>
                <td>aHCC8 (stageIII/<break />IV AJCC)</td>
                <td>SORA <italic>vs</italic>. no treatment</td>
                <td>0.24</td>
                <td>US$224,914</td>
                <td>US$100,000</td>
                <td>2.24</td>
                <td>Data were extracted from MEDICARE beneficiary’s dataset (SEER)<break /><break />Treated patients were matched with controls trough PSM<break /><break />Univariate and multivariate analyses were used to identify predictors of survival</td>
              </tr>
              <tr>
                <td>54</td>
                <td>Zhang <italic>et al</italic>.<sup>[<xref ref-type="bibr" rid="B87">87</xref>]</sup></td>
                <td>2015</td>
                <td>China</td>
                <td>aHCC</td>
                <td>SORA <italic>vs</italic>. BSC</td>
                <td>0.18</td>
                <td>US$101,399.11</td>
                <td>US$20,301.00</td>
                <td>4.99<break /><break />Costs are sensitive to Child-Pugh status</td>
                <td>Data extracted from medical records<break /><break />Markov model</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p><sup>a</sup>QALY is expressed as an increase or decrease versus the comparator; <sup>b</sup>ICER is expressed per QALY unit; <sup>c</sup>WTP is expressed per QALY unit; <sup>d</sup>If ICER/WTP &gt; 1, the treatment is not cost-effective in the context explored; <sup>e</sup>IBI305 is a bevacizumab biosimilar. CABO: Cabozantinib; BSC: best supportive care; aHCC: advanced hepatocellular carcinoma; QALY: quality-adjusted life year; LYS: life-years saved; ICER: incremental cost-effectiveness ratio; WTP: willingness to pay; USA: United States of America; UK: United Kingdom; REGO: regorafenib; uHCC: unresectable hepatocellular carcinoma; SORA: sorafenib; PEM: pembrolizumab; OS: overall survival; PFS: progression-free survival; RAMU: ramucirumab; AFP: alpha-fetoprotein; GDP: gross domestic product; AJCC: American Joint Committee on Cancer; SEER: Surveillance, Epidemiology, and End Results; PSM: propensity score matching.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap id="t5">
          <label>Table 5</label>
          <caption>
            <p>Summary of the risk bias evaluation of the 54 included studies according to the JBI<sup>[<xref ref-type="bibr" rid="B88">88</xref>]</sup></p>
          </caption>
          <table frame="hsides" rules="groups" pdfpage="18">
            <thead>
              <tr>
                <td style="border-bottom:1;">
                  <bold>Item</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>Remarks</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td>Is there a well-defined question?</td>
                <td>In all included studies</td>
              </tr>
              <tr>
                <td>Is there comprehensive description of alternatives?</td>
                <td>Only studies with multiple comparators<sup>[<xref ref-type="bibr" rid="B59">59</xref>-<xref ref-type="bibr" rid="B67">67</xref>]</sup><break />- All included studies except for references [<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B86">86</xref>,<xref ref-type="bibr" rid="B87">87</xref>] extracted data from previous phase II/III trials<break />- References [<xref ref-type="bibr" rid="B29">29</xref>,<xref ref-type="bibr" rid="B86">86</xref>,<xref ref-type="bibr" rid="B87">87</xref>] used real-world data without comprehensive description of alternatives</td>
              </tr>
              <tr>
                <td>Are all important and relevant costs and outcomes for each alternative identified?</td>
                <td>In all included studies</td>
              </tr>
              <tr>
                <td>Has clinical effectiveness been established?</td>
                <td>In all included studies</td>
              </tr>
              <tr>
                <td>Are costs and outcomes measured accurately?</td>
                <td>In all included studies except for references [<xref ref-type="bibr" rid="B59">59</xref>,<xref ref-type="bibr" rid="B68">68</xref>] where ICERs were not clearly reported</td>
              </tr>
              <tr>
                <td>Are costs and outcomes valued credibly?</td>
                <td>In all studies except for references [<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B82">82</xref>-<xref ref-type="bibr" rid="B84">84</xref>]<break />- Studies [<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B82">82</xref>,<xref ref-type="bibr" rid="B83">83</xref>] used higher WTPs than those recommended<break />- Reference [<xref ref-type="bibr" rid="B62">62</xref>] used a lower WTP than what usually recommended<break />- References [<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B84">84</xref>] did not report any WTP</td>
              </tr>
              <tr>
                <td>Are costs and outcomes adjusted for differential timing?</td>
                <td>In all included studies</td>
              </tr>
              <tr>
                <td>Is there an incremental analysis of costs and consequences?</td>
                <td>In all studies except for references [<xref ref-type="bibr" rid="B59">59</xref>,<xref ref-type="bibr" rid="B68">68</xref>]</td>
              </tr>
              <tr>
                <td>Were sensitivity analyses conducted to investigate uncertainty in estimates of cost or consequences?</td>
                <td>In all included studies except for reference [<xref ref-type="bibr" rid="B68">68</xref>]</td>
              </tr>
              <tr>
                <td>Do study results include all issues of concern to users?</td>
                <td>Only in studies [<xref ref-type="bibr" rid="B37">37</xref>,<xref ref-type="bibr" rid="B50">50</xref>,<xref ref-type="bibr" rid="B84">84</xref>]</td>
              </tr>
              <tr>
                <td>Are the results generalizable to the setting of interest in the review?</td>
                <td>With caution<break />- References [<xref ref-type="bibr" rid="B35">35</xref>,<xref ref-type="bibr" rid="B40">40</xref>-<xref ref-type="bibr" rid="B42">42</xref>,<xref ref-type="bibr" rid="B44">44</xref>-<xref ref-type="bibr" rid="B48">48</xref>,<xref ref-type="bibr" rid="B51">51</xref>-<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B60">60</xref>-<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B69">69</xref>,<xref ref-type="bibr" rid="B73">73</xref>,<xref ref-type="bibr" rid="B78">78</xref>,<xref ref-type="bibr" rid="B82">82</xref>,<xref ref-type="bibr" rid="B83">83</xref>,<xref ref-type="bibr" rid="B87">87</xref>] originate from or focus on the Chinese health market and may have a limited transferability to other international settings<break />- References [<xref ref-type="bibr" rid="B45">45</xref>-<xref ref-type="bibr" rid="B48">48</xref>,<xref ref-type="bibr" rid="B52">52</xref>-<xref ref-type="bibr" rid="B56">56</xref>,<xref ref-type="bibr" rid="B61">61</xref>,<xref ref-type="bibr" rid="B65">65</xref>-<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B69">69</xref>] included or focused on drugs that are currently limited to the Chinese healthcare market<break /><break />To assist in evaluation of current evidence, please refer to <inline-supplementary-material content-type="local-data" mimetype="application/pdf" xlink:href="-SupplementaryMaterials.pdf">Supplementary Table 1</inline-supplementary-material> for a list of drugs approved in the Chinese (NMPA), US (FDA) and European (EMA) markets</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p>JBI: Joanna Briggs Institute; ICER: incremental cost-effectiveness ratio; WTP: willingness to pay; NMPA: National Medical Products Administration; FDA: Food and Drug Administration; EMA: European Medicines Agency.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap id="t6">
          <label>Table 6</label>
          <caption>
            <p>Summary of qualitative evaluations of included comparative economic studies on systemic therapies for HCC obtained from the ECOBIAS toolkit<sup>[<xref ref-type="bibr" rid="B89">89</xref>]</sup></p>
          </caption>
          <table frame="hsides" rules="groups" pdfpage="19">
            <thead>
              <tr>
                <td style="border-bottom:1;">
                  <bold>Item</bold>
                </td>
                <td style="border-bottom:1;">
                  <bold>
                    <italic>N</italic> (%) studies</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td colspan="2">Type of studies</td>
              </tr>
              <tr>
                <td>CEA/CUA<sup>*</sup><break />CBA</td>
                <td>54 (100)<break />0 (0)</td>
              </tr>
              <tr>
                <td colspan="2">Countries explored</td>
              </tr>
              <tr>
                <td>China (%)<break />USA (%)<break />China-USA (%)<break />Taiwan (%)<break />Canada (%)<break />Japan (%)<break />Israel (%)<break />Germany-USA (%)<break />Singapore (%)<break />Thailand (%)<break />Italy (%)<break />France (%)<break />China-USA-Europe (%)<break />Australia (%)<break />Egypt (%)<break />India (%)<break />Brazil (%)</td>
                <td>26 (48.1)<break />6 (11.1)<break />4 (7.4)<break />2 (3.7)<break />2 (3.7)<break />2 (3.7)<break />2 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)<break />1 (1.8)</td>
              </tr>
              <tr>
                <td colspan="2">Data sourcing</td>
              </tr>
              <tr>
                <td>National/international registration trials<break />Real-world</td>
                <td>51 (94.4)<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B38">38</xref>,<xref ref-type="bibr" rid="B40">40</xref>-<xref ref-type="bibr" rid="B85">85</xref>]</sup><break />3 (5.6)<sup>[<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B86">86</xref>,<xref ref-type="bibr" rid="B87">87</xref>]</sup></td>
              </tr>
              <tr>
                <td colspan="2">Economic metrics</td>
              </tr>
              <tr>
                <td>Outcomes<break />    QALYs (%)<break />    LYS (%)<break />    ICER (%)<break />    ICUR (%)<break />    Alternative outcome measures (%)<break /><break />WTP (%)</td>
                <td>
                  <break />52 (96.3)<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B69">69</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup><break />15 (27.8)<sup>[<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B41">41</xref>,<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B46">46</xref>,<xref ref-type="bibr" rid="B50">50</xref>,<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B66">66</xref>,<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B75">75</xref>-<xref ref-type="bibr" rid="B77">77</xref>,<xref ref-type="bibr" rid="B80">80</xref>,<xref ref-type="bibr" rid="B84">84</xref>]</sup><break />49 (90.7)<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B42">42</xref>,<xref ref-type="bibr" rid="B44">44</xref>-<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B67">67</xref>-<xref ref-type="bibr" rid="B69">69</xref>,<xref ref-type="bibr" rid="B71">71</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B70">70</xref>]</sup><break />3 (5.5)<sup>[<xref ref-type="bibr" rid="B66">66</xref>,<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B74">74</xref>]</sup><break /><break />50 (92.6%)<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B69">69</xref>,<xref ref-type="bibr" rid="B72">72</xref>-<xref ref-type="bibr" rid="B83">83</xref>,<xref ref-type="bibr" rid="B85">85</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup></td>
              </tr>
              <tr>
                <td colspan="2">Methodology</td>
              </tr>
              <tr>
                <td>Partitioned survival analysis (%)<break />Markov model (%)<break />Other/not clearly reported (%)<break /><break />Lifetime horizon (%)<break />Defined horizon (%)<break />Median (IQR) years</td>
                <td>28 (51.8)<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B38">38</xref>-<xref ref-type="bibr" rid="B41">41</xref>,<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B47">47</xref>-<xref ref-type="bibr" rid="B50">50</xref>,<xref ref-type="bibr" rid="B53">53</xref>-<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B63">63</xref>,<xref ref-type="bibr" rid="B64">64</xref>,<xref ref-type="bibr" rid="B66">66</xref>,<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B69">69</xref>,<xref ref-type="bibr" rid="B70">70</xref>-<xref ref-type="bibr" rid="B72">72</xref>,<xref ref-type="bibr" rid="B75">75</xref>]</sup><break />23 (42.6)<sup>[<xref ref-type="bibr" rid="B37">37</xref>,<xref ref-type="bibr" rid="B42">42</xref>,<xref ref-type="bibr" rid="B44">44</xref>-<xref ref-type="bibr" rid="B46">46</xref>,<xref ref-type="bibr" rid="B51">51</xref>,<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B59">59</xref>,<xref ref-type="bibr" rid="B61">61</xref>,<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B73">73</xref>,<xref ref-type="bibr" rid="B74">74</xref>,<xref ref-type="bibr" rid="B76">76</xref>-<xref ref-type="bibr" rid="B78">78</xref>,<xref ref-type="bibr" rid="B80">80</xref>-<xref ref-type="bibr" rid="B85">85</xref>,<xref ref-type="bibr" rid="B87">87</xref>]</sup><break />3 (5.6)<sup>[<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B79">79</xref>,<xref ref-type="bibr" rid="B86">86</xref>]</sup><break /><break />15 (27.8)<sup>[<xref ref-type="bibr" rid="B35">35</xref>,<xref ref-type="bibr" rid="B37">37</xref>,<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B42">42</xref>,<xref ref-type="bibr" rid="B46">46</xref>-<xref ref-type="bibr" rid="B48">48</xref>,<xref ref-type="bibr" rid="B56">56</xref>,<xref ref-type="bibr" rid="B66">66</xref>,<xref ref-type="bibr" rid="B69">69</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B75">75</xref>,<xref ref-type="bibr" rid="B76">76</xref>,<xref ref-type="bibr" rid="B82">82</xref>,<xref ref-type="bibr" rid="B84">84</xref>]</sup><break />21 (38.9)<sup>[<xref ref-type="bibr" rid="B34">34</xref>,<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B38">38</xref>,<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B41">41</xref>,<xref ref-type="bibr" rid="B49">49</xref>,<xref ref-type="bibr" rid="B50">50</xref>,<xref ref-type="bibr" rid="B53">53</xref>,<xref ref-type="bibr" rid="B55">55</xref>,<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B61">61</xref>,<xref ref-type="bibr" rid="B63">63</xref>,<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B72">72</xref>,<xref ref-type="bibr" rid="B74">74</xref>,<xref ref-type="bibr" rid="B77">77</xref>,<xref ref-type="bibr" rid="B78">78</xref>,<xref ref-type="bibr" rid="B83">83</xref>,<xref ref-type="bibr" rid="B85">85</xref>]</sup><break />10 (9)</td>
              </tr>
              <tr>
                <td colspan="2">Perspective</td>
              </tr>
              <tr>
                <td>National/regional healthcare (%)<break />Payor (%)<break />Societal (%)<break />Not clearly indicated (%)</td>
                <td>18 (33.3)<sup>[<xref ref-type="bibr" rid="B34">34</xref>,<xref ref-type="bibr" rid="B44">44</xref>,<xref ref-type="bibr" rid="B46">46</xref>-<xref ref-type="bibr" rid="B48">48</xref>,<xref ref-type="bibr" rid="B56">56</xref>,<xref ref-type="bibr" rid="B57">57</xref>,<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B70">70</xref>-<xref ref-type="bibr" rid="B73">73</xref>,<xref ref-type="bibr" rid="B76">76</xref>,<xref ref-type="bibr" rid="B77">77</xref>,<xref ref-type="bibr" rid="B79">79</xref>,<xref ref-type="bibr" rid="B81">81</xref>]</sup><break />9 (16.7)<sup>[<xref ref-type="bibr" rid="B41">41</xref>-<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B45">45</xref>,<xref ref-type="bibr" rid="B49">49</xref>,<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B78">78</xref>,<xref ref-type="bibr" rid="B83">83</xref>,<xref ref-type="bibr" rid="B85">85</xref>]</sup><break />3 (5.5)<sup>[<xref ref-type="bibr" rid="B37">37</xref>,<xref ref-type="bibr" rid="B50">50</xref>,<xref ref-type="bibr" rid="B84">84</xref>]</sup><break />24 (44.4)<sup>[<xref ref-type="bibr" rid="B35">35</xref>,<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B38">38</xref>-<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B51">51</xref>-<xref ref-type="bibr" rid="B55">55</xref>,<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B59">59</xref>,<xref ref-type="bibr" rid="B61">61</xref>-<xref ref-type="bibr" rid="B64">64</xref>,<xref ref-type="bibr" rid="B66">66</xref>,<xref ref-type="bibr" rid="B69">69</xref>,<xref ref-type="bibr" rid="B74">74</xref>,<xref ref-type="bibr" rid="B75">75</xref>,<xref ref-type="bibr" rid="B80">80</xref>,<xref ref-type="bibr" rid="B82">82</xref>,<xref ref-type="bibr" rid="B86">86</xref>,<xref ref-type="bibr" rid="B87">87</xref>]</sup></td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p><sup>*</sup>Most CEA reported utility metrics. Therefore, a clear distinction between CEA and CUA is not an applicable measure. HCC: Hepatocellular carcinoma; CEA: cost-effectiveness analysis; CUA: cost-utility analysis; CBA: cost-benefit analysis; QALY: quality-adjusted life year; LYS: life-years saved; ICER: incremental cost-effectiveness ratio; ICUR: incremental cost-utility ratio; WTP: willingness to pay; IQR: interquartile range.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec id="sec2-4">
        <title>Ethic issues</title>
        <p>The current study was exempt from ethics committee review under Italian national regulations. This study was registered with the International Platform of Systematic Review and Meta-Analysis Protocols (INPLASY) at <uri xlink:href="http://www.inplasy.com">www.inplasy.com</uri> (#INPLASY2025100049; DOI: 10.37766/inplasy2025.10.0049).</p>
      </sec>
    </sec>
    <sec id="sec3">
      <title>RESULTS</title>
      <sec id="sec3-1">
        <title>Quantitative analysis</title>
        <p>The article-sorting algorithm is illustrated in <xref ref-type="fig" rid="fig1">Figure 1</xref>. We began with 30,500 references retrieved from the databases using “cost of treatment for HCC” as the primary keyword combination. Of these, 842 (100%) were retained, and their abstracts were screened for potential alignment with the study framework’s objectives, based on general hints of economic considerations. Finally, 164 (19.5%) references were selected for full-text review because they included economic analyses.</p>
        <fig id="fig1" position="float" width="500" pdfpage="6">
          <label>Figure 1</label>
          <caption>
            <p>The literature references selection algorithm. HAIC: Hepatic artery infusion therapy; HCC: hepatocellular carcinoma; RFA: radiofrequency ablation; SBRT: stereotactic body radiation therapy; SIRT: selective internal radiation therapy; TACE: trans-arterial chemoembolization.</p>
          </caption>
          <graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="hr11077.fig.1.jpg" />
        </fig>
        <p>Of the 164 studies (100%), 38 (23.2%) were excluded: 15 (9.1%) lacked a clear treatment comparator, 9 (5.5%) involved non-patients of interest, 7 (4.3%) were systematic reviews, 4 (2.3%) were duplicates, and one each focused on several cancer types (0.6%), did not include HCC patients (0.6%), or lacked suitable economic outcomes (0.6%). Ultimately, 126 studies (76.8%) were comparative economic analyses consistent with the research framework.</p>
        <p>Of these 126 (100%) studies, 72 (57.1%) were excluded because 16 (12.7%) focused on SIRT, 11 (8.7%) on TACE, 10 (7.9%) on surgical resection, 7 (5.6%) on transplantation, 7 (5.6%) on SBRT, 6 (4.8%) on RFA, 5 (3.4%) on HAIC, 4 (3.2%) on combination treatment, 4 (3.2%) on different treatment modalities, and 2 (1.6%) on HAIC ± systemic chemotherapy. Finally, 54 (42.8%) studies focused solely on systemic therapies and formed the core of this evaluation [<xref ref-type="fig" rid="fig1">Figure 1</xref> and <xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref>]<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>.</p>
        <p>Most of these studies examined the cost-effectiveness outcomes in China (26, 48.1%), six in the USA (11.1%), four in both China and the USA (7.4%), two in Taiwan (3.7%), two in Canada (3.7%), two in Japan (3.7%), two in Israel (3.7%), and one each in Germany and the USA (1.8%), Singapore (1.8%), Thailand (1.8%), Italy (1.8%), France (1.8%), China, USA, and Europe (1.8%), Australia (1.8%), Egypt (1.8%), India (1.8%), and Brazil (1.8%) [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t5">5</xref>, <xref ref-type="table" rid="t7">7</xref> and <xref ref-type="table" rid="t8">8</xref>].</p>
        <p>Owing to differences in study designs and drugs explored, we divided the retrieved comparative economic analyses into four categories: (1) head-to-head comparisons of ICIs as first-line therapy [usually against sorafenib (SORA)] as comparator [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B58">58</xref>]</sup>; (2) studies that simultaneously compared multiple ICI- and oral-based regimens as first-line treatment [<xref ref-type="table" rid="t2">Table 2</xref>]<sup>[<xref ref-type="bibr" rid="B59">59</xref>-<xref ref-type="bibr" rid="B68">68</xref>]</sup>; (3) studies on head-to-head comparison of oral agents only as first-line therapy [<xref ref-type="table" rid="t3">Table 3</xref>]; and (4) studies on first- or second-line therapies versus placebo and/or BSC [<xref ref-type="table" rid="t4">Table 4</xref>].</p>
      </sec>
      <sec id="sec3-2">
        <title>ICI as first-line therapy</title>
        <p>A total of 25 studies were included in this category [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B58">58</xref>]</sup>. Eleven studies focused on atezolizumab (ATE) [a programmed death-ligand 1 (PD-L1) inhibitor] + bevacizumab (BEVA) (a VEGF-A protein chain inhibitor)<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B44">44</xref>]</sup>; four studies examined sintilimab (SIN) + BEVA or BEVA biosimilar versus TKI/VEGFi [SORA in three cases, lenvatinib (LEN) in one]<sup>[<xref ref-type="bibr" rid="B45">45</xref>-<xref ref-type="bibr" rid="B48">48</xref>]</sup>; three studies compared the single tremelimumab (TREM) and regular-interval durvalumab (DUR) (STRIDE regimen) versus SORA<sup>[<xref ref-type="bibr" rid="B49">49</xref>-<xref ref-type="bibr" rid="B51">51</xref>]</sup>; two studies evaluated a combination of camrelizumab (CAM) + rivoceranib (RIV) against SORA<sup>[<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B53">53</xref>]</sup>; three studies assessed tislelizumab (TIS) versus SORA<sup>[<xref ref-type="bibr" rid="B54">54</xref>-<xref ref-type="bibr" rid="B56">56</xref>]</sup>; and two studies compared nivolumab (NIV) with SORA [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B57">57</xref>,<xref ref-type="bibr" rid="B58">58</xref>]</sup>.</p>
        <sec id="sec3-2-1">
          <title>ATE + BEVA</title>
          <p>The comparator was SORA in 10 (90.9%) studies<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B41">41</xref>-<xref ref-type="bibr" rid="B44">44</xref>]</sup>, and NIV in one (0.9%)<sup>[<xref ref-type="bibr" rid="B40">40</xref>]</sup>. All these studies based their economic analyses on the IMBrave-105 trial<sup>[<xref ref-type="bibr" rid="B90">90</xref>]</sup>. The analysis comparing ATE + BEVA <italic>vs</italic>. NIV also used data from the CheckMate-459 trial<sup>[<xref ref-type="bibr" rid="B91">91</xref>]</sup>. The studies were published between 2021 and 2025 and examined cost-effectiveness in China in four (36.4%), Taiwan in two (0.18%), and Thailand (0.9%), Singapore (0.9%), France (0.9%), the USA (0.9%), and both the USA and China (0.9%). The adjusted mean (SD) of ATE + BEVA QALYs was 0.70 ± 0.36, and the adjusted mean ± SD of LYS was 1.21 ± 0.11. The adjusted mean ± SD ICER/WTP ratio is 2.71 ± 3.07. Finally, ATE + BEVA was cost-effective (i.e., ICER/WTP &lt; 1) compared to the comparator in four studies (three versus SORA and one versus NIV) [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B38">38</xref>,<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B40">40</xref>]</sup>.</p>
        </sec>
        <sec id="sec3-2-2">
          <title>SIN + bevacizumab biosimilar</title>
          <p>Four studies published between 2021 and 2023 examined the cost-effectiveness of SIN (a PD-1 receptor antagonist approved for HCC in China) in combination with BEVA or a BEVA biosimilar (IBI3015)<sup>[<xref ref-type="bibr" rid="B44">44</xref>-<xref ref-type="bibr" rid="B48">48</xref>]</sup>. All of these studies were conducted by Chinese authors, with SORA as the comparator in three studies and LEN in one study<sup>[<xref ref-type="bibr" rid="B44">44</xref>-<xref ref-type="bibr" rid="B48">48</xref>]</sup>. The studies derived data for analysis from previous trials, that is ORIENT-32<sup>[<xref ref-type="bibr" rid="B92">92</xref>]</sup>, and REFLECT<sup>[<xref ref-type="bibr" rid="B93">93</xref>]</sup>. The adjusted mean ± SD of the SIN + BEVA biosimilar QALYs was 0.64 ± 0.42, and the reported LYS (measured in only one study) was 1.84. The adjusted mean ± SD ICER/WTP ratio is 1.06 ± 0.55. Finally, the SIN + BEVA biosimilar was cost-effective in three studies (two versus SORA, and one versus LEN) [<xref ref-type="table" rid="t1">Table 1</xref>].</p>
        </sec>
        <sec id="sec3-2-3">
          <title>STRIDE</title>
          <p>The STRIDE regimen was studied in three research projects between 2023 and 2025, involving scholars from the US (2 cases) and China (one)<sup>[<xref ref-type="bibr" rid="B49">49</xref>-<xref ref-type="bibr" rid="B51">51</xref>]</sup>. All studies used data from the HIMALAYA trial<sup>[<xref ref-type="bibr" rid="B94">94</xref>]</sup>. One study also compared DUR monotherapy with STRIDE<sup>[<xref ref-type="bibr" rid="B50">50</xref>]</sup>. The mean ± SD adjusted QALY for STRIDE was 0.35 ± 0.19, and the reported LYS (measured in only one study) was 0.27. The mean ± SD adjusted ICER/WTP ratio was 0.42 ± 0.26, and STRIDE proved cost-effective across all included studies, regardless of the TKI/VEGFi comparator<sup>[<xref ref-type="bibr" rid="B49">49</xref>-<xref ref-type="bibr" rid="B51">51</xref>]</sup>.</p>
        </sec>
        <sec id="sec3-2-4">
          <title>CAM + RIV</title>
          <p>A regimen combining CAM (a PD-1 inhibitor approved in China) with RIV (a VEGF-2 inhibitor approved in China and pending approval in other countries) was studied in two research projects by Chinese scholars, one examining China’s healthcare system and the other exploring both the US and Chinese healthcare systems [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B53">53</xref>]</sup>. Data were derived from the CARES-310 trial in both cases<sup>[<xref ref-type="bibr" rid="B95">95</xref>]</sup>. The adjusted mean ± SD QALY for CAM + RIV was 0.71 ± 0.08, and the adjusted mean ± SD ICER/WTP ratio was 0.71 ± 0.43. CAM + RIV was found to be cost-effective in both published studies<sup>[<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B53">53</xref>]</sup>.</p>
        </sec>
        <sec id="sec3-2-5">
          <title>TIS</title>
          <p>A single-agent regimen with TIS, a PD-1 inhibitor, was compared with SORA in three studies conducted by Chinese researchers, examining cost-effectiveness in China (two publications) and across China, the USA, and Europe (one publication) [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B54">54</xref>-<xref ref-type="bibr" rid="B56">56</xref>]</sup>. In all studies, data were derived from the RATIONALE-301 trial<sup>[<xref ref-type="bibr" rid="B96">96</xref>]</sup>, and the comparator was SORA. The adjusted mean ± SD QALY for TIS was 0.46 ± 0.18, and the adjusted mean ± SD ICER/WTP ratio was 0.58 ± 0.27. The regimen was cost-effective in all studies and across all international scenarios [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B54">54</xref>-<xref ref-type="bibr" rid="B56">56</xref>]</sup>.</p>
        </sec>
        <sec id="sec3-2-6">
          <title>NIV</title>
          <p>A single-agent regimen with NIV, a PD-1 inhibitor, was compared with SORA in two studies conducted between 2022 and 2023, both of which evaluated its cost-effectiveness in China<sup>[<xref ref-type="bibr" rid="B57">57</xref>,<xref ref-type="bibr" rid="B58">58</xref>]</sup>. Population data were obtained from the CheckMate-459 trial for each case<sup>[<xref ref-type="bibr" rid="B91">91</xref>]</sup>. Despite its improved clinical efficacy over SORA (i.e., adjusted mean ± SD QALY of 0.29 ± 0.03), NIV was not considered cost-effective in any of the studies (adjusted mean ± SD ICER/WTP ratio 3.83 ± 3.33) [<xref ref-type="table" rid="t1">Table 1</xref>]<sup>[<xref ref-type="bibr" rid="B57">57</xref>,<xref ref-type="bibr" rid="B58">58</xref>]</sup>.</p>
        </sec>
      </sec>
      <sec id="sec3-3">
        <title>Simultaneous comparison of multiple regimens</title>
        <p>Ten studies examined multiple first-line regimens simultaneously against a common comparator, usually SORA [<xref ref-type="table" rid="t2">Table 2</xref>]<sup>[<xref ref-type="bibr" rid="B59">59</xref>-<xref ref-type="bibr" rid="B68">68</xref>]</sup>.</p>
        <sec id="sec3-3-1">
          <title>Sequencing treatments</title>
          <p>In 2020, a US study examined eight different sequences of first- and second-line drugs using VEGFi and/or TKI agents [SORA, regorafenib (REGO), cabozantinib (CABO)], LEN, and ICIs [pembrolizumab (PEM), a PD-1 inhibitor, and NIV]<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup>. The sequences included SORA - REGO, SORA - CABO; SORA - NIV, SORA - PEM, LEN-REGO, CABO; LEN - LEN-NIV, and LEN-PEM [<xref ref-type="table" rid="t2">Table 2</xref>]. Data were obtained from randomized controlled trials (RCTs) of the respective drugs. Although utility outcomes (such as QALYs) were not available, the study indicated that a strategy of TKI/VEGFi followed by ICI upon disease progression is more cost-effective than using TKI/VEGF as both first- and second-line therapies<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup>. The two most cost-effective regimens were SORA - PEM (ICER = US$227,741.03) and LEN - PEM (US$230,371.17). However, both regimens were above the WTP national threshold of 150,000 USD<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup>.</p>
        </sec>
        <sec id="sec3-3-2">
          <title>Multiple comparisons</title>
          <p>Nine studies published between 2021 and 2024 compared multiple first-line regimens simultaneously<sup>[<xref ref-type="bibr" rid="B60">60</xref>-<xref ref-type="bibr" rid="B68">68</xref>]</sup>. Detailed information about the authors of the studies, publication years, national health systems examined, QALY/LYS, ICER, WTP, and ICER/WTP are shown in <xref ref-type="table" rid="t2">Table 2</xref>. Seven of these studies examined the cost-effectiveness of ICI- and TKI/VEGFi-based schedules together<sup>[<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B62">62</xref>-<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B68">68</xref>]</sup>; one focused only on TKI/VEGFi<sup>[<xref ref-type="bibr" rid="B66">66</xref>]</sup>, and one included only ICI therapies<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup>. Eight studies included SORA in their comparisons<sup>[<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B62">62</xref>-<xref ref-type="bibr" rid="B68">68</xref>]</sup>. In one study, the most cost-effective regimens were donafenib (DONA)<sup>[<xref ref-type="bibr" rid="B67">67</xref>]</sup>, a deuterium derivative of SORA approved for unresectable HCC in China in 2021<sup>[<xref ref-type="bibr" rid="B97">97</xref>,<xref ref-type="bibr" rid="B98">98</xref>]</sup>; DUR monotherapy<sup>[<xref ref-type="bibr" rid="B60">60</xref>]</sup>; SIN + BEVA biosimilar<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup>; ATE + BEVA<sup>[<xref ref-type="bibr" rid="B62">62</xref>]</sup>; CAM + RIV<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup>; LEN<sup>[<xref ref-type="bibr" rid="B62">62</xref>]</sup>, and sunitinib (SUN) [<xref ref-type="table" rid="t2">Table 2</xref>]<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup>.</p>
        </sec>
      </sec>
      <sec id="sec3-4">
        <title>Head-to-head comparison of oral agents</title>
        <p>Seven studies published between 2019 and 2022 evaluated the cost-effectiveness of oral agents through direct comparisons [<xref ref-type="table" rid="t3">Table 3</xref>]<sup>[<xref ref-type="bibr" rid="B69">69</xref>-<xref ref-type="bibr" rid="B75">75</xref>]</sup>. Six of these studies compared LEN to SORA<sup>[<xref ref-type="bibr" rid="B70">70</xref>-<xref ref-type="bibr" rid="B75">75</xref>]</sup>, whereas only one Chinese study compared DONA to SORA<sup>[<xref ref-type="bibr" rid="B69">69</xref>]</sup>. In all cases, data were obtained from published trials, including the ZDGH-3 phase 2 and 3 studies<sup>[<xref ref-type="bibr" rid="B98">98</xref>]</sup>, and the REFLECT trial<sup>[<xref ref-type="bibr" rid="B93">93</xref>]</sup>.</p>
        <p>Despite the increased QALY, a Chinese study reported that DONA was less cost-effective than SORA. However, its cost-effectiveness may increase in scenarios with a branded SORA formulation, lower DONA prices, and in high-income regions (ICER/WTP ratio of 0.42)<sup>[<xref ref-type="bibr" rid="B69">69</xref>]</sup>.</p>
        <p>All six studies on LEN demonstrated that this drug is a more cost-effective regimen than SORA<sup>[<xref ref-type="bibr" rid="B70">70</xref>-<xref ref-type="bibr" rid="B75">75</xref>]</sup>. In four of them, it was dominant over the comparator due to lower costs and higher utility (QALY) [<xref ref-type="table" rid="t3">Table 3</xref>]<sup>[<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B74">74</xref>,<xref ref-type="bibr" rid="B75">75</xref>]</sup>.</p>
      </sec>
      <sec id="sec3-5">
        <title>First and second-line therapies versus placebo and/or BSC</title>
        <p>A total of 12 studies were included in the final analysis [<xref ref-type="table" rid="t4">Table 4</xref>]<sup>[<xref ref-type="bibr" rid="B76">76</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>. Four analyses focused on CABO versus placebo/BSC after failure of first-line TKI/VEGFi therapy, using the CELESTIAL trial as the source dataset<sup>[<xref ref-type="bibr" rid="B99">99</xref>]</sup>. Two studies<sup>[<xref ref-type="bibr" rid="B80">80</xref>,<xref ref-type="bibr" rid="B81">81</xref>]</sup> involved REGO and were based on the RESORCE trial<sup>[<xref ref-type="bibr" rid="B100">100</xref>]</sup>. Two studies, each focusing on PEM<sup>[<xref ref-type="bibr" rid="B82">82</xref>]</sup> and ramucirumab (RAMU)<sup>[<xref ref-type="bibr" rid="B83">83</xref>]</sup>, were based on the KEYNOTE-240<sup>[<xref ref-type="bibr" rid="B101">101</xref>]</sup> and REACH-2 trials<sup>[<xref ref-type="bibr" rid="B102">102</xref>]</sup>, respectively.</p>
        <p>Four studies examined the cost-effectiveness of SORA compared to placebo/BSC as a first-line therapy<sup>[<xref ref-type="bibr" rid="B84">84</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>. Two studies<sup>[<xref ref-type="bibr" rid="B84">84</xref>,<xref ref-type="bibr" rid="B85">85</xref>]</sup> sourced data from the SHARP trial or from its Asia-Pacific population<sup>[<xref ref-type="bibr" rid="B103">103</xref>]</sup>. One study extracted data from the Surveillance and End Results (SEER) Medicare database<sup>[<xref ref-type="bibr" rid="B86">86</xref>]</sup>, whereas one Chinese study used medical records<sup>[<xref ref-type="bibr" rid="B87">87</xref>]</sup>. None of the studies demonstrated the cost-effectiveness of the research or active comparators. Detailed information on the study type, year of publication, country of origin, active treatment, QALYs, ICER, and ICER/WTP is reported in <xref ref-type="table" rid="t4">Table 4</xref>.</p>
      </sec>
      <sec id="sec3-6">
        <title>Overall</title>
        <p>Among the 54 included studies, 35 regimen comparisons were reported: 23 first-line (15 ICI-containing schedules and 8 TKI/VEGFi-based regimens), 4 second-line, and 8 sequencing treatments [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref> and <xref ref-type="table" rid="t7">7</xref>]. Eighteen active regimens were explored in China, 17 in the USA, and 5 in Europe, while other national markets were only minimally represented [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref> and <xref ref-type="table" rid="t6">6</xref>-<xref ref-type="table" rid="t8">8</xref>].</p>
        <p>A total of 14 (40.0%) active treatments were shown to be cost-effective. ICI-containing regimens were more frequently cost-effective than other systemic therapies [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref> and <xref ref-type="table" rid="t8">8</xref>]. Specifically, ATE + BEVA was cost-effective in five studies<sup>[<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B38">38</xref>-<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B62">62</xref>]</sup>, SIN + BEVA/BEVA biosimilar in four<sup>[<xref ref-type="bibr" rid="B46">46</xref>-<xref ref-type="bibr" rid="B48">48</xref>,<xref ref-type="bibr" rid="B61">61</xref>]</sup>, STRIDE in three<sup>[<xref ref-type="bibr" rid="B49">49</xref>-<xref ref-type="bibr" rid="B51">51</xref>]</sup>, CAM + RIV in three<sup>[<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B53">53</xref>,<xref ref-type="bibr" rid="B61">61</xref>]</sup>, TIS in three<sup>[<xref ref-type="bibr" rid="B54">54</xref>-<xref ref-type="bibr" rid="B56">56</xref>]</sup>, and DUR monotherapy in one<sup>[<xref ref-type="bibr" rid="B60">60</xref>]</sup>. Among oral agents (i.e., TKI/VEGFi), LEN was cost-effective in seven studies<sup>[<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B70">70</xref>-<xref ref-type="bibr" rid="B75">75</xref>]</sup>, while DONA and SUN were cost-effective in one study each<sup>[<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B67">67</xref>]</sup>. SORA was not cost-effective when compared with active comparators or BSC/placebo. The only exception was when a generic SORA formulation was compared with DONA due to the latter’s higher price<sup>[<xref ref-type="bibr" rid="B69">69</xref>]</sup>. The sequencing treatments SORA + PEM and LEN + PEM were cost-effective in one study of patients who failed initial therapy with oral agents<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup>.</p>
        <sec id="sec3-6-1">
          <title>Qualitative analysis</title>
          <p>All 54 studies were initially assessed for eligibility and risk of bias using the JBI assessment grid, which includes 11 items<sup>[<xref ref-type="bibr" rid="B88">88</xref>]</sup>. The detailed reports of these studies are shown in <xref ref-type="table" rid="t5">Table 5</xref>. Due to the large number of included studies, responses to the 11 items of the JBI are summarized collectively. Three qualitative items were poorly addressed across the included studies: (1) the comprehensive description of available therapeutic options; (2) the credibility of economic metrics; and (3) the transferability of results. No study evaluated all therapeutic regimens currently available in a specific health market. Cost-effectiveness metrics were not credibly reported in five studies: in four cases, WTPs exceeded those recommended by the WHO<sup>[<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B82">82</xref>,<xref ref-type="bibr" rid="B83">83</xref>]</sup>, and in one case, WTP was lower than that based on national GDP<sup>[<xref ref-type="bibr" rid="B62">62</xref>]</sup>. Four studies did not report any WTP<sup>[<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B84">84</xref>]</sup>. The transferability of results should be interpreted cautiously for studies exploring only the Chinese market (26 studies) or the Chinese market in combination with the USA (4 studies) or the USA and Europe (1 study), given the different dynamics of drug reimbursement policies [<xref ref-type="table" rid="t5">Tables 5</xref>-<xref ref-type="table" rid="t8">8</xref>]. Finally, 14 studies focused on or included drugs and regimens currently approved only in the Chinese market [<xref ref-type="table" rid="t5">Tables 5</xref>-<xref ref-type="table" rid="t8">8</xref>]. The <inline-supplementary-material content-type="local-data" mimetype="application/pdf" xlink:href="hr11077-SupplementaryMaterials.pdf">Supplementary Table 1</inline-supplementary-material> provides a complete list of systemic treatments approved in China, the USA, and Europe at the time of publication.</p>
		    <table-wrap id="t7">
            <label>Table 7</label>
            <caption>
              <p>Summary of treatments examined in the current systematic review</p>
            </caption>
            <table frame="hsides" rules="groups" pdfpage="20">
              <thead>
                <tr>
                  <td colspan="2" style="border-bottom:1;">
                    <bold>Treatments<sup>*</sup></bold>
                  </td>
                  <td style="border-bottom:1;">
                    <bold>
                      <italic>N</italic> (%) studies</bold>
                  </td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td colspan="3">First-line</td>
                </tr>
                <tr>
                  <td>Immunotherapy</td>
                  <td>ATE + BEVA versus SORA<break />ATE + BEVA with multiple comparators<break />ATE + BEVA versus NIV<break /><break />SIN + BEVAb versus SORA<break />SIN + BEVAb with multiple comparators<break />SIN + BEVAb versus LEN<break /><break />STRIDE versus SORA<break />STRIDE with multiple comparators<break />DUR versus SORA<break /><break />CAM + RIV versus SORA<break />CAM + RIV with multiple comparators<break /><break />PEM + LEN with multiple comparators<break /><break />TIS versus SORA<break /><break />NIV versus SORA</td>
                  <td>17 (31.5)<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B41">41</xref>-<xref ref-type="bibr" rid="B44">44</xref>,<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B62">62</xref>-<xref ref-type="bibr" rid="B68">68</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B40">40</xref>]</sup><break /><break />8 (14.8)<sup>[<xref ref-type="bibr" rid="B45">45</xref>,<xref ref-type="bibr" rid="B46">46</xref>,<xref ref-type="bibr" rid="B48">48</xref>,<xref ref-type="bibr" rid="B62">62</xref>-<xref ref-type="bibr" rid="B67">67</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B47">47</xref>]</sup><break /><break />4 (7.4)<sup>[<xref ref-type="bibr" rid="B49">49</xref>-<xref ref-type="bibr" rid="B51">51</xref>,<xref ref-type="bibr" rid="B60">60</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B50">50</xref>,<xref ref-type="bibr" rid="B60">60</xref>]</sup><break /><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B53">53</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup><break /><break />3 (5.6)<sup>[<xref ref-type="bibr" rid="B54">54</xref>-<xref ref-type="bibr" rid="B56">56</xref>]</sup><break /><break />3 (5.6)<sup>[<xref ref-type="bibr" rid="B57">57</xref>,<xref ref-type="bibr" rid="B58">58</xref>,<xref ref-type="bibr" rid="B62">62</xref>]</sup></td>
                </tr>
                <tr>
                  <td>TKI/VEGFi</td>
                  <td>SORA versus BSC/placebo<break /><break />LEN versus SORA<break /><break />DONA versus SORA<break />DONA versus LEN<break /><break />SUN versus SORA<break /><break />LIN versus SORA<break /><break />BRIVA versus SORA<break /><break />SORA + ERL versus SORA</td>
                  <td>4 (7.4)<sup>[<xref ref-type="bibr" rid="B84">84</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup><break /><break />12 (22.2)<sup>[<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B64">64</xref>-<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B70">70</xref>-<xref ref-type="bibr" rid="B75">75</xref>]</sup><break /><break />5 (9.2)<sup>[<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B65">65</xref>-<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B69">69</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B66">66</xref>]</sup><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup></td>
                </tr>
                <tr>
                  <td colspan="3">Second-line</td>
                </tr>
                <tr>
                  <td colspan="2">CABO versus BSC/placebo<break />REGO versus BSC/placebo<break />PEM versus BSC/placebo<break />RAMU versus BSC/placebo</td>
                  <td>4 (7.4)<sup>[<xref ref-type="bibr" rid="B76">76</xref>-<xref ref-type="bibr" rid="B79">79</xref>]</sup><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B80">80</xref>,<xref ref-type="bibr" rid="B81">81</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B82">82</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B83">83</xref>]</sup></td>
                </tr>
                <tr>
                  <td colspan="3">Sequencing treatments</td>
                </tr>
                <tr>
                  <td colspan="2">REGO after SORA<break />CABO after SORA<break />NIV after SORA<break />PEM after SORA<break />REGO after SORA<break />CABO after LEN<break />NIV after LEN<break />PEM after LEN</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup></td>
                </tr>
                <tr>
                  <td colspan="3">Active treatment by country/region explored<sup>**</sup></td>
                </tr>
                <tr>
                  <td>ASIA</td>
                  <td>China = 18 active treatments<break />ATE + BEVA<break />SIN + BEVAb<break />STRIDE<break />DUR<break />CAM + RIV<break />TIS<break />NIV<break />LEN<break />PEM + LEN<break />DONA<break />SUN<break />SORA + ERL<break />LIN<break />BRIVA<break />CABO<break />PEM<break />RAMU<break />SORA<break /><break />Japan = 2 active treatments<break />LEN<break /><break />Taiwan = 1 active treatment<break />ATE + BEVA<break /><break />Hong Kong = 1 active treatment<break />ATE + BEVA<break /><break />Singapore = 1 active treatment<break />ATE + BEVA<break /><break />Thailand = 1 active treatment<break />ATE + BEVA<break /><break />India = 1 active treatment<break />SORA</td>
                  <td>
                    <break />11 (20.4)<sup>[<xref ref-type="bibr" rid="B35">35</xref>,<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B41">41</xref>,<xref ref-type="bibr" rid="B44">44</xref>,<xref ref-type="bibr" rid="B60">60</xref>-<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B67">67</xref>]</sup><break />10 (18.5)<sup>[<xref ref-type="bibr" rid="B45">45</xref>-<xref ref-type="bibr" rid="B48">48</xref>,<xref ref-type="bibr" rid="B61">61</xref>-<xref ref-type="bibr" rid="B65">65</xref>,<xref ref-type="bibr" rid="B67">67</xref>]</sup><break />3 (5.6)<sup>[<xref ref-type="bibr" rid="B51">51</xref>,<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B61">61</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B60">60</xref>]</sup><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B53">53</xref>]</sup><break />4 (25.9)<sup>[<xref ref-type="bibr" rid="B54">54</xref>-<xref ref-type="bibr" rid="B56">56</xref>,<xref ref-type="bibr" rid="B61">61</xref>]</sup><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B57">57</xref>,<xref ref-type="bibr" rid="B58">58</xref>]</sup><break />12 (22.2)<sup>[<xref ref-type="bibr" rid="B60">60</xref>,<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B64">64</xref>-<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B70">70</xref>-<xref ref-type="bibr" rid="B75">75</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup><break />5 (9.2)<sup>[<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B65">65</xref>-<xref ref-type="bibr" rid="B67">67</xref>,<xref ref-type="bibr" rid="B69">69</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B78">78</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B82">82</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B83">83</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B87">87</xref>]</sup><break /><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B75">75</xref>]</sup><break /><break /><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B34">34</xref>,<xref ref-type="bibr" rid="B38">38</xref>]</sup><break /><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B42">42</xref>]</sup><break /><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B36">36</xref>]</sup><break /><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B37">37</xref>]</sup><break /><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B84">84</xref>]</sup></td>
                </tr>
                <tr>
                  <td>Asia-Pacific</td>
                  <td>Australia = 1 active treatment<break />LEN</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B72">72</xref>]</sup></td>
                </tr>
                <tr>
                  <td>North America</td>
                  <td>USA = 17 active treatments<break />ATE + BEVA<break />NIV<break />STRIDE<break />DUR<break />TIS<break />LEN<break />SORA-REGO<break />SORA-CABO<break />SORA-NIV<break />SORA-PEN<break />LEN-REGO<break />LEN-CABO<break />LEN-NIV<break />LEN-PEM<break />CABO<break />REGO<break />SORA<break /><break />Canada <break />LEN</td>
                  <td>3 (5.6)<sup>[<xref ref-type="bibr" rid="B35">35</xref>,<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B62">62</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B62">62</xref>]</sup><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B49">49</xref>,<xref ref-type="bibr" rid="B50">50</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B50">50</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B54">54</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B62">62</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B76">76</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B81">81</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B86">86</xref>]</sup><break /><break /><break />2 (3.7)<sup>[<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B74">74</xref>]</sup></td>
                </tr>
                <tr>
                  <td>Middle East</td>
                  <td>Israel = 2 active treatments<break />CABO<break />REGO</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B77">77</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B80">80</xref>]</sup></td>
                </tr>
                <tr>
                  <td>Africa</td>
                  <td>Egypt = 1 active treatment<break />SORA</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B85">85</xref>]</sup><break /></td>
                </tr>
                <tr>
                  <td>Europe</td>
                  <td>Europe = 1 active treatment<break />TIS<break /><break />France = 1 active treatment<break />ATE + BEVA<break /><break />Italy = 2 active treatments<break />ATE + BEVA<break />LEN<break /><break />Germany = 1 active treatment<break />CABO</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B54">54</xref>]</sup><break /><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B39">39</xref>]</sup><break /><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B68">68</xref>]</sup><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B68">68</xref>]</sup><break /><break /><break />1 (1.8)<sup>[<xref ref-type="bibr" rid="B76">76</xref>]</sup><break /></td>
                </tr>
                <tr>
                  <td>South America</td>
                  <td>Brazil = 1 active treatment<break />CABO</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B79">79</xref>]</sup></td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn>
                <p><sup>*</sup>As monotherapy, combined therapies or sequencing treatments; <sup>**</sup>SORA was considered only as an active treatment when the comparator was placebo or supportive care. ATE: Atezolizumab; BEVA: bevacizumab; NIV: nivolumab; SIN: sintilimab; BEVAb: bevacizumab biosimilar; LEN: lenvatinib; STRIDE: single tremelimumab regular interval durvalumab; DUR: durvalumab; CAM: camrelizumab; RIV: rivoceranib; PEM: pembrolizumab; TIS: tislelizumab; TKI: tyrosine kinase inhibitor; VEGFi: vascular endothelial growth factor inhibitors or antagonists; SORA: sorafenib; BSC: best supportive care; DONA: donafenib; SUN: sunitinib; LIN: linifanib; BRIVA: brivanib; ERL: erlotinib; CABO: cabozantinib; REGO: regorafenib; RAMU: ramucirumab.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
          <table-wrap id="t8">
            <label>Table 8</label>
            <caption>
              <p>Summary of cost-effective treatments based on the results of the systematic review</p>
            </caption>
            <table frame="hsides" rules="groups" pdfpage="22">
              <tbody>
                <tr>
                  <td>
                    <bold>Treatments<sup>*</sup></bold>
                  </td>
                  <td>
                    <bold>
                      <italic>N</italic> (%) studies</bold>
                  </td>
                  <td>
                    <bold>Countries explored</bold>
                  </td>
                </tr>
                <tr>
                  <td colspan="3">First-line</td>
                </tr>
                <tr>
                  <td colspan="3">Immunotherapy</td>
                </tr>
                <tr>
                  <td>ATE + BEVA <italic>vs.</italic> SORA</td>
                  <td>5 (9.2)<sup>[<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B38">38</xref>,<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B62">62</xref>]</sup></td>
                  <td>China (1), Singapore (1), Taiwan (1), USA (1), France (1)</td>
                </tr>
                <tr>
                  <td>ATE + BEVA <italic>vs.</italic> NIV</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B40">40</xref>]</sup></td>
                  <td>China (1)</td>
                </tr>
                <tr>
                  <td>SIN + BEVAb <italic>vs.</italic> SORA</td>
                  <td>3 (5.6)<sup>[<xref ref-type="bibr" rid="B46">46</xref>,<xref ref-type="bibr" rid="B47">47</xref>,<xref ref-type="bibr" rid="B48">48</xref>]</sup></td>
                  <td>China (3)</td>
                </tr>
                <tr>
                  <td>SIN + BEVAb <italic>vs.</italic> multiple comparators</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup></td>
                  <td>China (1)</td>
                </tr>
                <tr>
                  <td>STRIDE <italic>vs.</italic> SORA</td>
                  <td>3 (5.6)<sup>[<xref ref-type="bibr" rid="B49">49</xref>,<xref ref-type="bibr" rid="B50">50</xref>,<xref ref-type="bibr" rid="B51">51</xref>]</sup></td>
                  <td>USA (2), China (1)</td>
                </tr>
                <tr>
                  <td>CAM + RIV <italic>vs.</italic> SORA</td>
                  <td>2 (3.7)<sup>[<xref ref-type="bibr" rid="B52">52</xref>,<xref ref-type="bibr" rid="B53">53</xref>]</sup></td>
                  <td>China (2), USA (1) (study #53 explored both the Chinese and the US market)</td>
                </tr>
                <tr>
                  <td>CAM + RIV <italic>vs.</italic> multiple comparators</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B61">61</xref>]</sup></td>
                  <td>China (1)</td>
                </tr>
                <tr>
                  <td>TIS <italic>vs.</italic> SORA</td>
                  <td>3 (5.6)<sup>[<xref ref-type="bibr" rid="B54">54</xref>,<xref ref-type="bibr" rid="B55">55</xref>,<xref ref-type="bibr" rid="B56">56</xref>]</sup></td>
                  <td>China (3), USA (1), Europe (1) (study #54 explored China, USA, and Europe)</td>
                </tr>
                <tr>
                  <td>DUR <italic>vs.</italic> SORA</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B60">60</xref>]</sup></td>
                  <td>China (1), USA (1) (study #60 explored both China and USA)</td>
                </tr>
                <tr>
                  <td colspan="3">TKI/VEGFi</td>
                </tr>
                <tr>
                  <td>LEN <italic>vs.</italic> SORA</td>
                  <td>7 (12.9)<sup>[<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B72">72</xref>,<xref ref-type="bibr" rid="B73">73</xref>,<xref ref-type="bibr" rid="B74">74</xref>,<xref ref-type="bibr" rid="B75">75</xref>]</sup></td>
                  <td>China (3), USA (1), Canada (2), Japan (2), Australia (1) (study #62 explored both China and USA)</td>
                </tr>
                <tr>
                  <td>DONA <italic>vs.</italic> SORA</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B67">67</xref>]</sup></td>
                  <td>China (1)</td>
                </tr>
                <tr>
                  <td>SUN <italic>vs.</italic> multiple comparators</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B65">65</xref>]</sup></td>
                  <td>China (1)</td>
                </tr>
                <tr>
                  <td colspan="3">Sequencing treatments</td>
                </tr>
                <tr>
                  <td>SORA-PEM</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup></td>
                  <td>USA (1)</td>
                </tr>
                <tr>
                  <td>LEN-PEM</td>
                  <td>1 (1.8)<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup></td>
                  <td>USA (1)</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn>
                <p><sup>*</sup>As monotherapy, combined therapies or sequencing treatments. ATE: Atezolizumab; BEVA: bevacizumab; NIV: nivolumab; SIN: sintilimab; BEVAb: bevacizumab biosimilar; STRIDE: single tremelimumab regular interval durvalumab; CAM: camrelizumab; RIV: rivoceranib; TIS: tislelizumab; DUR: durvalumab; TKI: tyrosine kinase inhibitor; VEGFi: vascular endothelial growth factor inhibitors or antagonists; LEN: lenvatinib; DONA: donafenib; SUN: sunitinib; SORA: sorafenib; PEM: pembrolizumab.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
          <p>Further assessments were performed using the ECOBIAS checklist<sup>[<xref ref-type="bibr" rid="B89">89</xref>]</sup>, as shown in <xref ref-type="table" rid="t6">Table 6</xref>. Metrics of utility, such as QALYs, were reported in nearly all included studies (52 = 96.3%), whereas effectiveness measures, such as LYS, were reported in 15 (27.8%) studies [<xref ref-type="table" rid="t6">Table 6</xref>]. ICERs were reported in 49 (90.7%) studies, with 2 (3.7%) using ICURs<sup>[<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B70">70</xref>]</sup>. Three studies (5.5%) employed alternative outcome measures such as cost savings or ICER per month of PFS<sup>[<xref ref-type="bibr" rid="B66">66</xref>,<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B74">74</xref>]</sup>. WTPs were documented in all studies except 4 (92.6%)<sup>[<xref ref-type="bibr" rid="B68">68</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B84">84</xref>]</sup>. Notably, no CBA has been reported in the international literature on systemic therapies for advanced HCC during the study period.</p>
          <p>Almost all studies collected data from published trials on systemic therapies or from network meta-analyses of published trials (51/54, 94.4%)<sup>[<xref ref-type="bibr" rid="B90">90</xref>-<xref ref-type="bibr" rid="B103">103</xref>]</sup>. This limited the ability to accurately count patients included in the review, owing to the risk of double-counting participants from the trials used for cost-comparative assessments. Real-world data were only available from a study in France on ATE + BEVA<sup>[<xref ref-type="bibr" rid="B39">39</xref>]</sup>, a survey of SORA from the USA using SEER program (<uri xlink:href="https://seer.cancer.gov/registries/">https://seer.cancer.gov/registries/</uri>)<sup>[<xref ref-type="bibr" rid="B86">86</xref>]</sup>, and a study from China comparing SORA to placebo/BSC<sup>[<xref ref-type="bibr" rid="B87">87</xref>]</sup>. Most studies (28/54, 51.8%) used a partitioned survival model, which included PFS, progressive disease (PD), and death, to estimate cost-effectiveness [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref>]. Twenty-three studies (42.6%) employed a Markov state-transition model, one (1.8%) used a decision analytic approach<sup>[<xref ref-type="bibr" rid="B79">79</xref>]</sup>, one combined propensity score matching with univariate and multivariate survival analysis<sup>[<xref ref-type="bibr" rid="B86">86</xref>]</sup>, and one (1.8%) did not clearly specify the methodology for calculating transitions across health states for patients on systemic therapy [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref>]<sup>[<xref ref-type="bibr" rid="B68">68</xref>]</sup>. A lifetime horizon was used to estimate the costs of the therapies in 15 studies (27.8%) [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t6">6</xref>]. In 21 studies (38.9%), the median [interquartile range (IQR)] timeframe was 10 (9) years [<xref ref-type="table" rid="t5">Tables 5</xref> and <xref ref-type="table" rid="t6">6</xref>]. However, this was not clearly specified in the remaining 18 studies (33.3%) [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref>].</p>
          <p>A national or regional healthcare system perspective was used in 18 studies (33.3%). A payor’s perspective was employed in nine studies (16.7%), whereas a societal perspective was adopted in three studies (5.5%). It was not clearly specified in 24 studies (44.4%) [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t6">6</xref>].</p>
          <p>
            <xref ref-type="table" rid="t7">Tables 7</xref> and <xref ref-type="table" rid="t8">8</xref> provide details on the types and numbers of treatments explored, as well as their distribution across countries. While the overall number of treatments differs only slightly between China and the USA, more treatments were investigated more than once in China [<xref ref-type="table" rid="t7">Table 7</xref>]. In Chinese studies, among 18 treatments/regimens, LEN was investigated 12 times; ATE + BEVA, 11 times; SIN + BEVA biosimilar, 10 times; DONA, 5 times; and TIS, 4 times. Further treatments were investigated  3 times [<xref ref-type="table" rid="t7">Table 7</xref>]. Of the 17 treatments investigated in US papers, the most frequently explored were ATE + BEVA (3 times)<sup>[<xref ref-type="bibr" rid="B35">35</xref>,<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B62">62</xref>]</sup>; and STRIDE (2 times)<sup>[<xref ref-type="bibr" rid="B49">49</xref>,<xref ref-type="bibr" rid="B50">50</xref>]</sup>. In Europe, only 5 treatments were explored, with ATE + BEVA being the most frequently investigated regimen (2 times)<sup>[<xref ref-type="bibr" rid="B39">39</xref>,<xref ref-type="bibr" rid="B68">68</xref>]</sup>.</p>

        </sec>
      </sec>
    </sec>
    <sec id="sec4">
      <title>DISCUSSION</title>
      <p>Although effectiveness is the primary outcome measure for any new therapy, CEAs are crucial for informed decision-making. This is especially true when multiple therapies are available for a specific disease or when several options emerge within a short period<sup>[<xref ref-type="bibr" rid="B104">104</xref>]</sup>. This situation applies to HCC, for which treatment options have expanded since 2008 with the introduction of systemic therapies<sup>[<xref ref-type="bibr" rid="B90">90</xref>-<xref ref-type="bibr" rid="B103">103</xref>]</sup>. The primary goal of CEAs is to identify strategies that maximize health benefits with available resources or improve the value of money<sup>[<xref ref-type="bibr" rid="B104">104</xref>]</sup>. In recent years, the number of cost-effectiveness publications related to HCC has increased<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>. This trend mirrors the growing number of publications on the cost-effectiveness of treatment options for stroke, neurological diseases, and cardiovascular conditions<sup>[<xref ref-type="bibr" rid="B104">104</xref>]</sup>. However, the implications and limitations of this field remain poorly understood by clinicians<sup>[<xref ref-type="bibr" rid="B105">105</xref>]</sup>.</p>
      <p>Systemic therapies are transforming the care of patients with HCC<sup>[<xref ref-type="bibr" rid="B13">13</xref>]</sup>, and they are increasingly used in clinical practice not only as first- or second-line treatments but also in combination with radiology-assisted techniques, surgery, and LT<sup>[<xref ref-type="bibr" rid="B14">14</xref>]</sup>. The current arsenal of systemic therapies includes various drug categories, ranging from oral agents (typically TKIs and VEGFi) to ICIs<sup>[<xref ref-type="bibr" rid="B13">13</xref>]</sup>. Within each category, differences exist in target molecular mechanisms, pharmacodynamics, pharmacokinetic properties, routes of administration, and side effects<sup>[<xref ref-type="bibr" rid="B13">13</xref>]</sup>. These characteristics affect not only the drug’s effectiveness but also its clinical utility and economic burden.</p>
      <p>To assess the cost-effectiveness of systemic therapies for HCC, we conducted a systematic review covering the past decade. Following the PRISMA framework, we used a narrative approach to summarize the findings because international studies varied greatly in research methods, data sources, time horizons, sensitivity analyses, case-scenario simulations, perspectives, and the countries studied [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t6">6</xref>]<sup>[<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B22">22</xref>,<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>.</p>
      <sec id="sec4-1">
        <title>Main findings</title>
        <sec id="sec4-1-1">
          <title>First-line regimens</title>
          <p>Overall, the main finding of our review was that 14 (40.0%) of the 35 treatments compared in the literature demonstrated some degree of cost-effectiveness, with only a third of the included studies (18/54) reporting it [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref>, <xref ref-type="table" rid="t7">7</xref> and <xref ref-type="table" rid="t8">8</xref>]. These treatments included 9 first-line ICI-containing regimens, 3 first-line TKI/VEGFi schedules, and 2 sequencing treatments [<xref ref-type="table" rid="t8">Table 8</xref>]. Among first-line treatments, ICI-containing regimens were more often cost-effective than other active drug regimens<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>, and LEN outperformed SORA more frequently than the other targeted oral agents (i.e., DONA, SUN). These results align with the superior clinical effectiveness of these regimens in phase II and III trials [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref>, <xref ref-type="table" rid="t7">7</xref> and <xref ref-type="table" rid="t8">8</xref>].</p>
          <p>Finally, despite its widespread use until the introduction of LEN and/or ICI-containing regimens, SORA was not proven to be cost-effective compared to placebo or BSC<sup>[<xref ref-type="bibr" rid="B84">84</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>. However, no study has evaluated the ICER of generic SORA formulations introduced into clinical practice over the past few years. The lack of these studies is likely due to SORA’s inferior clinical effectiveness compared to more recent LEN and/or ICIs.</p>
        </sec>
        <sec id="sec4-1-2">
          <title>Second-line regimens</title>
          <p>Second-line therapies after the failure of initial oral agents have not shown cost-effectiveness for any of the drugs studied (CABO, REGO, PEM, and RAM) when compared to placebo or BSC<sup>[<xref ref-type="bibr" rid="B76">76</xref>-<xref ref-type="bibr" rid="B83">83</xref>]</sup>. This is because the limited improvements in OS and PFS do not justify the high costs of these medications. Only one US study evaluated the cost-effectiveness of eight treatment sequences involving both first- and second-line agents<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup>. Despite limitations from a multiple-comparator analysis using data from randomized clinical trials of six different agents, the study found that two combinations were cost-effective: SORA-PEM and LEN-PEM<sup>[<xref ref-type="bibr" rid="B59">59</xref>]</sup>. However, these results should be revisited given the proven superiority of ICIs over SORA as first-line options.</p>
          <p>Overall, these findings from comparative economic analyses of first- and second-line agents/regimens do not conflict with clinical data but instead underscore the economic burden of introducing new drugs into the healthcare market. Drug prices were the main cost factor in all the included studies, and strategies to reduce these costs may lower the value of ICERs and enhance the ICER/WTP ratios<sup>[<xref ref-type="bibr" rid="B42">42</xref>,<xref ref-type="bibr" rid="B43">43</xref>,<xref ref-type="bibr" rid="B70">70</xref>,<xref ref-type="bibr" rid="B71">71</xref>,<xref ref-type="bibr" rid="B74">74</xref>,<xref ref-type="bibr" rid="B75">75</xref>,<xref ref-type="bibr" rid="B81">81</xref>,<xref ref-type="bibr" rid="B82">82</xref>]</sup>.</p>
        </sec>
      </sec>
      <sec id="sec4-2">
        <title>Limitations</title>
        <sec id="sec4-2-1">
          <title>Geographical distribution</title>
          <p>An important finding of this research is that most studies were conducted by Chinese authors or focused on the Chinese medical market<sup>[<xref ref-type="bibr" rid="B34">34</xref>-<xref ref-type="bibr" rid="B87">87</xref>]</sup>. Overall, 48.1% (26/54) of the papers examined only the Chinese market, 4 (7.4%) combined China and the USA, and one (1.8%) investigated the Chinese, US, and European markets. This is due to the epidemiological importance of HCC in China, as well as the fact that more first- and second-line agents have been approved for use in China than in other countries or regions [<inline-supplementary-material content-type="local-data" mimetype="application/pdf" xlink:href="hr11077-SupplementaryMaterials.pdf">Supplementary Table 1</inline-supplementary-material>]. To our knowledge, 14 drugs or treatment regimens have been approved for advanced HCC in China as of the publication of this paper, and at least nine targeted agents or combination regimens were recommended by experts in 2024, including SORA, LEN, DONA, ATE + BEVA, SIN + BEVA/BEVA biosimilar, and second-line options such as REGO, CABO, and apatinib.</p>
          <p>However, this apparent dominance decreased when comparing the number of treatments studied across different countries or regions, especially for China and the USA [<xref ref-type="table" rid="t7">Table 7</xref>]. Despite having more publications, the number of regimens examined was nearly the same in Chinese papers (<italic>n</italic> = 18) and studies from the USA (<italic>n</italic> = 17) [<xref ref-type="table" rid="t1">Tables 1</xref>-<xref ref-type="table" rid="t4">4</xref> and <xref ref-type="table" rid="t7">7</xref>]. Topic redundancy was observed among Chinese researchers, who studied LEN in 12 publications, ATE + BEVA in 11, SIN + BEVA biosimilar in 10, DONA in 5, and TIS in 3 [<xref ref-type="table" rid="t7">Table 7</xref>]. A clear reason for this redundancy is hard to determine but may be linked to publication pressure on Chinese researchers, the size of China’s healthcare market, the epidemiology of HCC in China<sup>[<xref ref-type="bibr" rid="B106">106</xref>]</sup>, the complex economic factors across different Chinese regions, and the requirements for obtaining marketing approval from Chinese authorities. Lastly, various Chinese pharmaceutical companies have developed and produced a significant portion of systemic drugs for HCC, including CAM, RIV, SIN, various BEVA biosimilars, and DONA, and they obtained marketing approval earlier than in other countries [<inline-supplementary-material content-type="local-data" mimetype="application/pdf" xlink:href="hr11077-SupplementaryMaterials.pdf">Supplementary Table 1</inline-supplementary-material>].</p>
          <p>This geographical imbalance in the literature on systemic treatments for HCC calls for caution when applying the review’s conclusions to countries outside China and Asia. Macroeconomic factors (such as national GDPs, WTPs, drug reimbursement policies, patient co-payments, drug pricing, discount rates, manufacturer competition, regulation of generic versus brand-name products, <italic>etc</italic>.) and microeconomic elements (like access to care and medications, patients’ social status, neighborhood deprivation, availability of family support or caregivers, <italic>etc</italic>.) are not always clearly included in comparative economic analyses and continue to affect the benefits and usefulness of systemic drug treatments for advanced HCC.</p>
        </sec>
        <sec id="sec4-2-2">
          <title>Methodology of included studies</title>
          <p>Several key issues were identified across the studies included in this review, as shown in <xref ref-type="table" rid="t5">Tables 5</xref> and <xref ref-type="table" rid="t6">6</xref>. Only a small number of studies addressed multiple comparators<sup>[<xref ref-type="bibr" rid="B59">59</xref>-<xref ref-type="bibr" rid="B67">67</xref>]</sup>, and only a few were based on real-world data<sup>[<xref ref-type="bibr" rid="B29">29</xref>,<xref ref-type="bibr" rid="B86">86</xref>,<xref ref-type="bibr" rid="B87">87</xref>]</sup>. This is because nearly all studies relied on phase II/III trials<sup>[<xref ref-type="bibr" rid="B90">90</xref>-<xref ref-type="bibr" rid="B103">103</xref>]</sup>, with limited use of post-registration clinical evidence. With the notable exception of SORA, which was approved for use in the USA, Europe, and China between 2007 and 2008, and oxaliplatin-containing regimens approved in China in 2013, all other systemic agents have been approved more recently, from 2017 onward [<inline-supplementary-material content-type="local-data" mimetype="application/pdf" xlink:href="hr11077-SupplementaryMaterials.pdf">Supplementary Table 1</inline-supplementary-material>]<sup>[<xref ref-type="bibr" rid="B106">106</xref>,<xref ref-type="bibr" rid="B107">107</xref>]</sup>.</p>
          <p>Post-registration, clinically focused economic analyses are crucial for better linking evidence to real-world practice. This is because initial drug prices typically decrease over time due to annual discounts, contracting, and competition from new therapies. Additionally, as treatments evolve, approved indications often expand to include patient groups not covered in registration trials<sup>[<xref ref-type="bibr" rid="B90">90</xref>-<xref ref-type="bibr" rid="B103">103</xref>]</sup>. Patient selection in randomized clinical trials is usually stricter than in real-world settings, and exclusion criteria - such as bleeding, ascites, and liver decompensation - remain relevant for many patients needing treatment, especially considering their shorter lifespan<sup>[<xref ref-type="bibr" rid="B90">90</xref>-<xref ref-type="bibr" rid="B103">103</xref>]</sup>. Finally, issues like temporary drug withdrawal, dose adjustments due to adverse events, and the use of surgery, radiological procedures, or switching drugs are not addressed in the original trials used for marketing authorization. Therefore, it is not surprising that the societal perspective was considered in only a small percentage of the included studies (5.5%), and that issues of concern to patients (e.g., access to care, work disability, loss of income, <italic>etc</italic>.) were overlooked in the current review.</p>
        </sec>
        <sec id="sec4-2-3">
          <title>Review sufficiency</title>
          <p>We acknowledge that, since our review relies on the published literature, it may not encompass all relevant economic analyses on the topic. First, financial information on HCC treatments may be shared not only through scientific publications but also via manufacturers’ reports, drug leaflets, digital media coverage, and administrative sources. Additionally, economic evaluations of systemic drug treatments might have been communicated only to hospital administrators and/or policymakers, rather than being included in peer-reviewed reports or publications. Furthermore, adjustments are often needed in health economic studies to account for inflation, disparities in resource allocation methods, and differences in pricing and reimbursement policies [such as disease-related group (DRG) tariffs, co-pays, and out-of-pocket systems]. These adjustments are not always reflected in scientific reports and often require experience with a specific national or regional market to incorporate them into comparative economic analyses. Finally, elements of current economic instability - such as increased tariffs on exports to the USA and reduced availability of components from manufacturing countries - can undermine the reliability of analyses and forecasts.</p>
        </sec>
        <sec id="sec4-2-4">
          <title>Results transferability</title>
          <p>The transferability of the results of this review should therefore be interpreted with caution and considered within the context of each national or regional setting where systemic drugs for advanced HCC are used. Aside from the geographical differences and the methodological limitations previously mentioned, the ultimate cost-effectiveness of systemic treatments depends on the ICER/WTP ratio. The WHO guidelines recommend that the national WTP be set at a level aligned with per capita GDP, ranging from 1 to 3 times that amount<sup>[<xref ref-type="bibr" rid="B33">33</xref>]</sup>. Since GDPs vary across and within countries, ICER/WTP ratios differ between studies and over time. Furthermore, although ICER/WTP measures access to treatment in a specific scenario, it often does not fully reflect true cost-effectiveness. National or regional health authorities and administrators may override this ratio for treatments with proven clinical importance, such as those for malignancies or rare diseases, especially when effective options are limited. Policymakers and stakeholders might also implement policies that reallocate financial resources from less effective treatments to more costly ones, thereby increasing access for underserved populations.</p>
          <p>Interestingly, the method commonly used to evaluate the cost-effectiveness of systemic therapies for advanced HCC in this review relies on direct comparisons between treatment regimens or schedules, such as ICI-containing regimens versus VEGFi. In nearly all included studies, SORA was used as the standard control against the experimental treatment arm(s). Although this reflects the design of the registration trials used for comparative economic calculations, real-world data suggest a shift from SORA to LEN, a decrease in the use of oral agents as first-line therapies following the advent of ICIs, and an increase in their use as second-line treatments for patients with limited tumor progression<sup>[<xref ref-type="bibr" rid="B108">108</xref>,<xref ref-type="bibr" rid="B109">109</xref>]</sup>.</p>
          <p>Finally, the comparative approach used in the reviewed papers faces challenges due to the increasing adoption of combination strategies in clinical practice for the treatment of advanced HCC<sup>[<xref ref-type="bibr" rid="B14">14</xref>,<xref ref-type="bibr" rid="B108">108</xref>,<xref ref-type="bibr" rid="B109">109</xref>]</sup>. While systemic therapies were initially viewed as alternatives for patients with advanced tumors who were ineligible for surgery (including resection and LT) or radiology-guided procedures, the current clinical landscape shows a growing use of combination approaches. These include systemic therapies, such as neo-adjuvant or adjuvant treatments, or bridging modalities to enhance surgical or radiological outcomes<sup>[<xref ref-type="bibr" rid="B108">108</xref>,<xref ref-type="bibr" rid="B109">109</xref>]</sup>. One example of these innovative approaches is the recent approval by Chinese authorities of PEM in combination with LEN and TACE, emphasizing the need for appropriate methodologies to evaluate their cost-effectiveness in real-world settings.</p>
        </sec>
        <sec id="sec4-2-5">
          <title>How can the cost-effectiveness of systemic therapies be improved?</title>
          <p>Building on the analysis of accessible comparative economic data, the secondary goal of this review was to raise awareness of strategies to enhance the cost-effectiveness of systemic therapies for advanced HCC. These strategies are shown in <xref ref-type="table" rid="t9">Table 9</xref> and are based on Bronfenbrenner’s ecological systems theory<sup>[<xref ref-type="bibr" rid="B110">110</xref>]</sup>, which suggests that implementing interventions should involve three levels: the micro-level (the healthcare provider-patient dyad), the meso-level (healthcare organizations), and the macro-level (administrators, policymakers, stakeholders, and society at large). These initiatives should engage all participants involved in caring for patients with advanced HCC, including patients, healthcare providers, healthcare organizations, administrators, policymakers, stakeholders, and scientific societies, and should develop suitable methods to address the complexities of caring for advanced HCC patients.</p>
          <table-wrap id="t9">
            <label>Table 9</label>
            <caption>
              <p>A list of suggested initiatives to increase the cost-effectiveness of systemic therapies for advanced HCC</p>
            </caption>
            <table frame="hsides" rules="groups" displaytype="1">
              <thead>
                <tr>
                  <td style="border-bottom:1;">
                    <bold>Level</bold>
                  </td>
                  <td style="border-bottom:1;">
                    <bold>Initiative(s)</bold>
                  </td>
                  <td style="border-bottom:1;">
                    <bold>Expected outcome(s)</bold>
                  </td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td>Micro (patient-healthcare provider interaction)</td>
                  <td>- Integration of multidisciplinary competencies/teams in clinical settings<break />- Education/training of healthcare professionals on systemic therapies with special consideration to ICI-containing schedules and combination approaches<break />- Close monitoring of patients’ adverse effects, well-being, quality of life by integration of remote assistance approaches whenever possible<break />- Empowerment of patients and family care givers to increase awareness, preparation and self-management<break />- Prompt treatment of adverse effects<break />- Regular follow-up visits</td>
                  <td>- Improvement of treatment effectiveness<break />- Reduction of patients’ non-adherence<break />- Reduction/mitigation of drug-related adverse effects<break />- Improvement of patients’ QoL<break />- Improvement of patients’ access to care<break />- Reduction of the economic burden related to the incidence of adverse events, ancillary treatments and referrals<break />- Reduction of physical and work disability<break />- Improvement of LYSs, QALYs and ICERs</td>
                </tr>
                <tr>
                  <td>Meso (healthcare organizations)</td>
                  <td>- Appointment of multidisciplinary teams for the treatment of HCC<break />- Facilitation of competency integration into clinical practice<break />- Facilitation of clinical data collection<break />- Facilitation of interventional pharmacoeconomics, i.e., structured efficiency models to optimize treatment dosages, exposures, and durations<break />- Implementation of real-world clinical studies<break />- Implementation of care pathways within and across healthcare institutions to facilitate patient access to care<break />- Care givers and stakeholders’ involvement in the decision-making process</td>
                  <td>- Improvement of treatment appropriateness<break />- Reduction of unnecessary treatments<break />- Improvement of drug-related side effects management<break />- Integration of individual and societal concerns into clinical data collection</td>
                </tr>
                <tr>
                  <td>Macro (administrators, policy makers, stakeholders)</td>
                  <td>- Promotion of generic and biosimilar substitution<break />- Shifting of reimbursement models from volume-based to outcome-based strategies<break />- Facilitation of HTA models for advanced HCC<break />- International referencing pricing, i.e., comparing international prices to adjust costs at regional/national levels<break />- Implementation of publicly funded clinical trials to assess cost-effectiveness in real-world settings<break />- Increase administrative efficiency to reduce overhead costs associated with drug contracting<break />- Reduced approval timelines to accelerate drug marketing<break />- Resource shifting according to disease epidemiology<break />- Facilitation of public discourse on the economic metrics to be adopted for treatment of advanced HCC<break />- Involvement of scientific societies and key opinion leaders in designing economic models to capture the economic metrics of cancer treatments</td>
                  <td>- Reduction of drug prices<break />- Increase of annual drug discount rates<break />- Cost savings from reorganization of administrative models supporting drug delivery<break />- Introduction of more reliable economic metrics to capture the complexities of cancer treatments</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn>
                <p>HCC: Hepatocellular carcinoma; ICI: immune checkpoint inhibitor; QoL: quality of life; LYS: life-years saved; QALY: quality-adjusted life year; ICER: incremental cost-effectiveness ratio; HTA: health technology assessment.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
          <p>In conclusion, our systematic review highlights significant variability in comparative economic analyses of systemic therapies for HCC across and within national and international settings. These differences mainly arise from study methodologies, time horizons, drug costs, and the perspectives used (such as societal versus healthcare systems), rather than from the sources of the datasets. However, based on current evidence, ICIs tend to be more cost-effective as first-line agents than any other active comparators studied. Among the oral agents, LEN is more cost-effective than SORA, and both SORA-PEM and LEN-PEM appear to be the most cost-effective sequencing strategies in the single study investigating these drug sequences. Changes in clinical practice, driven by the expansion of systemic therapies beyond their original indications and their combination with radiology-assisted techniques or surgery, necessitate aligning the methodologies of future studies with economic evaluations. A standardized approach to cost-effectiveness research, along with regular updates, is therefore essential given the rapidly evolving clinical landscape and the need to offer patients the highest standard of care.</p>
        </sec>
      </sec>
    </sec>
  </body>
  <back>
    <sec>
      <title>DECLARATIONS</title>
      <sec>
        <title>Acknowledgments</title>
        <p>The authors owe a deep debt of gratitude to the administrative staff of the Department of Surgical, Medical, Biomolecular Pathology and Intensive Care, University of Pisa, Pisa, Italy.</p>
      </sec>
      <sec>
        <title>Authors’ contributions</title>
        <p>Conceived the study: De Simone P, Campani D, Vistoli F</p>
        <p>Developed the research strings: Ducci J, Romano L, Longo D</p>
        <p>Evaluated the abstracts: Longo D, De Simone P, Peritore D</p>
        <p>Collected the full-length papers and extracted the data: Longo D, Peritore D, Romano L, Ducci J</p>
        <p>Drafted the manuscript: De Simone P, Longo D</p>
        <p>Assessed the manuscript and addressed critical issues: Giuliani A, Vistoli F</p>
        <p>All authors read and approved the final manuscript.</p>
      </sec>
      <sec>
        <title>Availability of data and materials</title>
        <p>The papers included in this analysis, along with their evaluation of inclusion and exclusion criteria, were stored on the Ryyan platform. Individual credentials secure access to data. Data will be made available upon request.</p>
      </sec>
      <sec>
        <title>AI and AI-assisted tools statement</title>
        <p>During the preparation of this manuscript, the AI tools Rayyan and Grammarly were used solely for literature screening/management and language editing, respectively. These tools did not influence the study design, data collection, analysis, interpretation, or the scientific content of the work. All authors take full responsibility for the accuracy, integrity, and final content of the manuscript.</p>
      </sec>
      <sec>
        <title>Financial support and sponsorship</title>
        <p>None.</p>
      </sec>
      <sec>
        <title>Conflicts of interest</title>
        <p>De Simone P is an Editorial Board Member of <italic>Hepatoma Research</italic>. De Simone P was not involved in any stage of the editorial process, including reviewer selection, manuscript handling, or decision-making. The other authors declared that there are no conflicts of interest.</p>
      </sec>
      <sec>
        <title>Ethical approval and consent to participate</title>
        <p>Not applicable.</p>
      </sec>
      <sec>
        <title>Consent for publication</title>
        <p>Not applicable.</p>
      </sec>
      <sec>
    <title>Copyright</title>
    <p>&#x00A9; The Author(s) 2026.</p>
      </sec>
      <sec sec-type="supplementary-material">
      <title>Supplementary Materials</title>
          <supplementary-material content-type="local-data">
                <media xlink:href="hr11077-SupplementaryMaterials.pdf" mimetype="application/pdf">
                        <caption>
                                <p>Supplementary Materials</p>
                        </caption>
                </media>
          </supplementary-material>
          </sec>
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